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Diagnostic profile characteristics of cancer patients with frequent consultations in primary care before diagnosis: a case-control study

Diagnostic profile characteristics of cancer patients with frequent consultations in primary care... Abstract Background Many patients with common cancers are late diagnosed. Objectives Identify consultation profiles and clinical features in patients with the seven most common cancers, who had consulted a general practitioner (GP) frequently before their cancer diagnosis. Methods A case-control study was conducted in Region Västra Götaland, Sweden. A total of 2570 patients, diagnosed in 2011 with prostate, breast, colorectal, lung, gynaecological and skin cancers including malignant melanoma, and 9424 controls were selected from the Swedish Cancer Register and a regional health care database. Diagnostic codes [International Statistical Classification of Diseases and Related Health Problems, 10th revision (ICD-10)] from primary care for patients with ≥4 GP consultations registered in the year before cancer diagnosis were collected. Likelihood ratios (LRs) were calculated for variables associated with the different cancers. Results Fifty-six percent of the patients had consulted a GP four or more times in the year before cancer diagnosis. Alarm symptoms or signs represented 60% of the codes with the highest LR, but only 40% of the 10 most prevalent codes. Breast lump had the highest LR, 11.9 [95% confidence interval (CI) 8.0–17.8]; abnormalities of plasma proteins had an LR of 5.0 (95% CI 3.0–8.2) and abnormal serum enzyme levels had an LR of 4.6 (95% CI 3.6–5.9). Early clinical features associated with cancer had been registered already at the first two GP consultations. Conclusion One out of six clinical features associated with cancer were presented by cancer patients with four or more pre-referral consultations already at the two first consultations. These early clinical features that were focal and had benign characteristics might have been missed diagnostic opportunities. Cancer, consultation, diagnosis, general practice, ICD codes, primary health care Introduction Despite great advances in diagnostics and the treatment of cancer, many of the most common cancers are diagnosed at an advanced stage. There has been a lack of consensus over whether a delay in cancer diagnosis truly affects survival (1–3). However, there is growing evidence that screening and early detection of symptomatic cancer results in a better prognosis for the patient (4–11). Our knowledge about clinical features of different cancers has, until quite recently, come from research in secondary care. Yet, more than two-thirds of all cancers are diagnosed in primary care (8,12–16). An increased consultation rate in primary care before a cancer diagnosis has been reported in the literature (17–21). Not only the clinical benefit of timely cancer diagnosis but also patient preferences and patient experience have to be considered. There is now evidence of a negative association between multiple pre-diagnostic consultations with a general practitioner (GP) and the experience of subsequent cancer care (22). The challenge for the GP is to identify the relatively few cancer patients among the many patients who present with symptoms and clinical features that are mostly the same for benign and for malignant diseases. Alarm symptoms are clinical features that are considered to predict serious, often malignant disease, for example, unexplained lump in breast for breast cancer and rectal bleeding for colorectal cancer. The majority of urgent referral pathways for cancer that are now implemented in the UK and several Scandinavian countries are based on the presentation of these features. In the UK, features with a positive predictive value (PPV) of 3% or higher that are defined in the NICE guidelines warrant urgent referral and appointment within 2 weeks (4,23). Cancer can also present with vague, unspecific symptoms that have unspecific origin (14,24). However, even when features are focal, derived from a specific organ and having the characteristics of a benign condition, the underlying cause can be that of cancer (21). Sweden is well known for its total population databases, which is why a case-control study was conducted using the regional database for health care and the National Cancer Register. This study aimed to identify the diagnostic profiles including potential missed diagnostic opportunities both in relation to the sequence of consultations and cancer type, in cancer patients with four or more GP consultations in the year before cancer diagnosis. Methods Study design A population-based case-control study was designed using the Swedish Cancer Register (SCR) and a regional health care database in Region Västra Götaland (RVG), Sweden. This region, which has 1.6 million inhabitants (17% of the Swedish population), is situated in the south-west of Sweden and includes rural and urban areas. The SCR, which was established in 1958, is one of the oldest disease registers in the world and has high validity (25). All physicians, including pathologists, in Sweden are obliged by law to report all incident cases of cancer from both living and dead patients to the SCR (26). Each patient has a unique personal identity number that all Swedish residents acquire either at birth or when they immigrate to Sweden. The regional health care database was established in RVG in 2000. It covers all hospitals, specialized outpatient care and all private and public primary health care centres. The database includes the patient’s Swedish personal identity number, place of residence, age, sex, health care contacts and diagnostic codes for diagnoses and surgical procedures (27). At each consultation, physicians are obliged to enter the codes for a patient’s current disease(s) or symptoms into the patient’s medical records. The reimbursement system for primary care providers is partly based on the disease burden of the patients, which is defined by diagnostic codes reported to this database. Study population Cases eligible for the study were identified from the SCR for the period 1 January 2011 to 31 December 2011. Inclusion criteria were as follows: diagnosed in RVG with one of the seven most common cancers—prostate cancer, breast cancer, colorectal cancer, lung cancer, gynaecological cancer or skin cancers, including malignant melanoma; alive at the time of the cancer diagnosis; aged ≥18 years and consulted a GP four or more times during the year before cancer diagnosis. Individuals were excluded from participation if they lacked a control and had a previous cancer diagnosis in the SCR (1991–2010). The patients with an earlier cancer diagnosis were deliberately omitted to avoid consultations in primary care being a control or concern of a previous cancer. Controls were selected from the regional health care database. They had the same inclusion criteria as the patients with cancer, with the exception of the cancer diagnosis. Four controls were matched to each case on age, sex and primary care unit. Matching of patients and controls had to be done before retrieving data regarding diagnostic codes and consultation dates from the regional health care database. A final selection of patients and controls with four or more consultations was then made, and therefore, not all patients retained four controls. Data collection The unique personal identity numbers of both cases and controls were linked to the regional health care database. All data concerning diagnoses and dates of consultations with a GP between 1 January 2010 and 31 December 2011 were collected. For the cases, only diagnostic codes before the date of their cancer diagnosis were collected. The data extracted included diagnostic codes according to the following: Swedish version of the International Statistical Classification of Diseases and Related Health Problems, 10th revision (ICD-10) or Classification of Diseases and Health Problems 1997 Primary Care (KSH97-P)—this is an abbreviated version of ICD-10, adapted to Swedish primary care to facilitate diagnostic coding (28–30). Diagnostic codes All the diagnostic codes registered when the cases and their controls consulted a GP during the study period were studied. As more than 6000 different diagnostic codes were received, their number was reduced by merging the four-character diagnostic codes to the closest three-character diagnostic codes according to clinical relevance (19). This was done because the incidence of the individual ICD-10 codes was too low to conduct statistical analyses. Finally, 575 codes remained that occurred in ≥1% of either cases or controls. The codes represented both diseases, symptoms and clinical findings such as laboratory results, and so henceforth they will be referred to as clinical features. Data analyses The 575 diagnostic codes were then used for univariable conditional logistic regression at significance level 0.01. Those diagnostic codes found to be associated with cancer were then analysed to see to which cancer they were associated. The likelihood ratio (LR) was then calculated. LR is a measure that expresses the probability of any clinical finding in patients with a disorder divided by the probability of the same finding in patients without the disorder (31). The LR was computed for all seven cancers combined as the study aimed to reflect the whole panorama of different symptoms/features of the most common cancers presented to the GPs. After this procedure, the codes were sorted in consultation order and organized into two groups: ‘early clinical features’ where a great proportion of them had been registered at the two first consultations and less than 75% after the fourth or a later consultation and ‘late clinical features’ where more than 75% were first presented at the fourth or a later GP consultation. All analyses were performed using the statistical software R (version 3.0.1). Results Cases and controls As the flowchart of the study sample recruitment process shows (Fig. 1), 2570 cancer patients fulfilled all inclusion and exclusion criteria. Because 269 controls died before their cases were diagnosed with cancer and 587 did not have four or more visits in primary care, there were not always four controls for each case. This resulted in 9424 controls in the final sample. Characteristics of the sample are outlined in Table 1. Of the patients with the seven most common cancers in this study, who had consulted a GP in the year prior to cancer diagnosis, 56% had four or more face-to-face consultations (Fig. 1). Figure 1 View largeDownload slide Sample recruitment flowchart Figure 1 View largeDownload slide Sample recruitment flowchart Table 1 Cancer patients that consulted primary care four or more times the year prior to cancer diagnosis Characteristics Cancer patients ≥4 consultations, n = 2570 (%) Controls ≥4 consultations, n = 9424 (%) Proportion of the individual cancers in the total cancer sample with no regard to no. of consultations, n = 4562 (%) Prostate cancer 637 (25) 2443 (51) Breast cancer 456 (18) 2028 (48) Colorectal cancer 493 (19) 1600 (65) Lung cancer 245 (10) 799 (66) Malignant melanoma 240 (9) 886 (52) Skin cancer 294 (11) 950 (66) Gynaecological cancer 205 (8) 718 (63) Female 1337 (52) 5020 (53) Male 1233 (48) 4404 (47) Median age at diagnosis, years (range) 71 (29–97) 70 (29–97) <60 years 491 (19) 1967 (21) 60–80 years 1553(60) 5769 (61) >80 years 526 (20) 1688 (18) Median number of consultations per patient in year before cancer diagnosis, n (IQR) 7 (5–10) 7 (5–10) Median number of unique diagnostic codes per patient in year before cancer diagnosis, n (IQR) 8 (5–11) 8 (6–11) Characteristics Cancer patients ≥4 consultations, n = 2570 (%) Controls ≥4 consultations, n = 9424 (%) Proportion of the individual cancers in the total cancer sample with no regard to no. of consultations, n = 4562 (%) Prostate cancer 637 (25) 2443 (51) Breast cancer 456 (18) 2028 (48) Colorectal cancer 493 (19) 1600 (65) Lung cancer 245 (10) 799 (66) Malignant melanoma 240 (9) 886 (52) Skin cancer 294 (11) 950 (66) Gynaecological cancer 205 (8) 718 (63) Female 1337 (52) 5020 (53) Male 1233 (48) 4404 (47) Median age at diagnosis, years (range) 71 (29–97) 70 (29–97) <60 years 491 (19) 1967 (21) 60–80 years 1553(60) 5769 (61) >80 years 526 (20) 1688 (18) Median number of consultations per patient in year before cancer diagnosis, n (IQR) 7 (5–10) 7 (5–10) Median number of unique diagnostic codes per patient in year before cancer diagnosis, n (IQR) 8 (5–11) 8 (6–11) IQR, interquartile range. View Large Table 1 Cancer patients that consulted primary care four or more times the year prior to cancer diagnosis Characteristics Cancer patients ≥4 consultations, n = 2570 (%) Controls ≥4 consultations, n = 9424 (%) Proportion of the individual cancers in the total cancer sample with no regard to no. of consultations, n = 4562 (%) Prostate cancer 637 (25) 2443 (51) Breast cancer 456 (18) 2028 (48) Colorectal cancer 493 (19) 1600 (65) Lung cancer 245 (10) 799 (66) Malignant melanoma 240 (9) 886 (52) Skin cancer 294 (11) 950 (66) Gynaecological cancer 205 (8) 718 (63) Female 1337 (52) 5020 (53) Male 1233 (48) 4404 (47) Median age at diagnosis, years (range) 71 (29–97) 70 (29–97) <60 years 491 (19) 1967 (21) 60–80 years 1553(60) 5769 (61) >80 years 526 (20) 1688 (18) Median number of consultations per patient in year before cancer diagnosis, n (IQR) 7 (5–10) 7 (5–10) Median number of unique diagnostic codes per patient in year before cancer diagnosis, n (IQR) 8 (5–11) 8 (6–11) Characteristics Cancer patients ≥4 consultations, n = 2570 (%) Controls ≥4 consultations, n = 9424 (%) Proportion of the individual cancers in the total cancer sample with no regard to no. of consultations, n = 4562 (%) Prostate cancer 637 (25) 2443 (51) Breast cancer 456 (18) 2028 (48) Colorectal cancer 493 (19) 1600 (65) Lung cancer 245 (10) 799 (66) Malignant melanoma 240 (9) 886 (52) Skin cancer 294 (11) 950 (66) Gynaecological cancer 205 (8) 718 (63) Female 1337 (52) 5020 (53) Male 1233 (48) 4404 (47) Median age at diagnosis, years (range) 71 (29–97) 70 (29–97) <60 years 491 (19) 1967 (21) 60–80 years 1553(60) 5769 (61) >80 years 526 (20) 1688 (18) Median number of consultations per patient in year before cancer diagnosis, n (IQR) 7 (5–10) 7 (5–10) Median number of unique diagnostic codes per patient in year before cancer diagnosis, n (IQR) 8 (5–11) 8 (6–11) IQR, interquartile range. View Large Diagnostic codes All 575 variables were used for univariate logistic regression, and this resulted in 34 statistically significant variables (P-value < 0.01) with LR higher than one. The diagnostic codes for neoplasm of uncertain or unknown behaviour, of female organs, oral cavity or digestive organs, and of carcinoma in situ of skin were removed from all cancer cases with no regard to cancer type because the study focused on clinical features present before the cancer diagnosis, and these codes more or less signalled the cancer diagnosis. After also removing the diagnostic code for ‘other medical care’, 26 remaining variables had a LR higher than 1.5, but only 24 had a prevalence higher than 1% and were retained (Table 2). Between 59% and 94% of the diagnostic codes were first registered at the patients’ fourth or later GP consultation. Six out of ten of the codes with the highest LR were alarm symptoms for cancer; however, when sorted for how prevalent they were in the cancer population, only 4 out of the 10 turned out to be alarm symptoms. Table 2 First time registered diagnostic codes (P-value < 0.01), their prevalence in cases, probability expressed in LR and relation to order of consultation Diagnostic codes ICD-10a Diagnostic codes, N Prev. >1% LR (95% CI) Visit 1 + 2b, n (%) Visit ≥4, n (%) N63 Lump in breast 101 3.9 11.9 (8.0–17.8) 5 (4.9) 95 (94.1) R77 Other abnormalities of plasma proteins 37 1.4 5.0 (3.0–8.2) 9 (24.3) 25 (67.6) R74 Abnormal serum enzyme levels 138 5.4 4.6 (3.6–5.9) 36 (26.0) 88 (63.8) R19.0 Intra-abdominal and pelvic swelling, mass and lump 30 1.2 4.4 (2.6–7.5] 0 28 (93.3) L85 Other epidermal thickening 32 1.2 4.3 (2.6–7.2] 3 (9.4) 27 (84.4) R19.4 Change in bowel habit 55 2.1 3.7 (2.5–5.3) 10 (18.2) 39 (70.9) N95.0 Postmenopausal bleeding 64 2.5 3.7 (2.6–5.2] 8 (12.5) 50 (78.1) K92.2 Gastrointestinal haemorrhage 28 1.1 3.5 (2.1–5.9) 2 (7.1) 22 (78.6) K62.5 Rectal bleeding 28 1.1 3.5 (2.1–5.9) 3 (10.7) 23 (82.1) K92.1 Melaena 40 1.6 3.5 (2.3–5.4) 5 (12.5) 30 (75.0) K92 Other diseases of digestive system 30 1.2 3.1 (1.9–5.1) 8 (26.7) 20 (66.7) R79 Other abnormal findings of blood chemistry 48 1.9 2.7 (1.9–3.9) 6 (12.5) 37 (77.1) K62 Other diseases of anus and rectum 84 3.3 2.7 (2.0–3.5) 11 (13.1) 67 (79.8) D12 Benign neoplasm of colon, rectum, anus and anal canal 38 1.5 2.7 (1.8–4.1) 5 (13.2) 29 (76.3) N83 Non-inflammatory disorders of ovary, fallopian tube and broad ligament 33 1.3 2.6 (1.7–4.1) 5 (15.2) 23 (69.7) D50 Iron deficiency anaemia 105 4.1 2.6 (2.0–3.3) 22 (20.9) 74 (70.5) R33 Retention of urine 95 3.7 2.4 (1.8–3.0) 25 (26.3) 58 (61.0) N42 Other disorders of prostate 101 3.9 2.3 (1.8–3.0) 28 (27.7) 66 (65.3) R31 Haematuria 71 2.7 2.2 (1.6–3.0) 17 (23.9) 46 (64.8) N40 Hyperplasia of prostate 331 12.9 2.0 (1.8–2.3) 92 (27.8) 213 (64.3) R23 Other skin changes 306 11.9 1.8 (1.6–2.1) 54 (17.6) 224 (73.2) D22 Melanocytic naevi 97 3.8 1.8 (1.4–2.3) 25 (25.8) 57 (58.8) L57.0 Actinic keratosis 173 6.7 1.8 (1.5–2.1) 44 (25.4) 114 (65.9) D64 Other anaemias 197 7.7 1.8 (1.5–2.1) 28 (14.2) 149 (75.6) 2262 451 1604 Diagnostic codes ICD-10a Diagnostic codes, N Prev. >1% LR (95% CI) Visit 1 + 2b, n (%) Visit ≥4, n (%) N63 Lump in breast 101 3.9 11.9 (8.0–17.8) 5 (4.9) 95 (94.1) R77 Other abnormalities of plasma proteins 37 1.4 5.0 (3.0–8.2) 9 (24.3) 25 (67.6) R74 Abnormal serum enzyme levels 138 5.4 4.6 (3.6–5.9) 36 (26.0) 88 (63.8) R19.0 Intra-abdominal and pelvic swelling, mass and lump 30 1.2 4.4 (2.6–7.5] 0 28 (93.3) L85 Other epidermal thickening 32 1.2 4.3 (2.6–7.2] 3 (9.4) 27 (84.4) R19.4 Change in bowel habit 55 2.1 3.7 (2.5–5.3) 10 (18.2) 39 (70.9) N95.0 Postmenopausal bleeding 64 2.5 3.7 (2.6–5.2] 8 (12.5) 50 (78.1) K92.2 Gastrointestinal haemorrhage 28 1.1 3.5 (2.1–5.9) 2 (7.1) 22 (78.6) K62.5 Rectal bleeding 28 1.1 3.5 (2.1–5.9) 3 (10.7) 23 (82.1) K92.1 Melaena 40 1.6 3.5 (2.3–5.4) 5 (12.5) 30 (75.0) K92 Other diseases of digestive system 30 1.2 3.1 (1.9–5.1) 8 (26.7) 20 (66.7) R79 Other abnormal findings of blood chemistry 48 1.9 2.7 (1.9–3.9) 6 (12.5) 37 (77.1) K62 Other diseases of anus and rectum 84 3.3 2.7 (2.0–3.5) 11 (13.1) 67 (79.8) D12 Benign neoplasm of colon, rectum, anus and anal canal 38 1.5 2.7 (1.8–4.1) 5 (13.2) 29 (76.3) N83 Non-inflammatory disorders of ovary, fallopian tube and broad ligament 33 1.3 2.6 (1.7–4.1) 5 (15.2) 23 (69.7) D50 Iron deficiency anaemia 105 4.1 2.6 (2.0–3.3) 22 (20.9) 74 (70.5) R33 Retention of urine 95 3.7 2.4 (1.8–3.0) 25 (26.3) 58 (61.0) N42 Other disorders of prostate 101 3.9 2.3 (1.8–3.0) 28 (27.7) 66 (65.3) R31 Haematuria 71 2.7 2.2 (1.6–3.0) 17 (23.9) 46 (64.8) N40 Hyperplasia of prostate 331 12.9 2.0 (1.8–2.3) 92 (27.8) 213 (64.3) R23 Other skin changes 306 11.9 1.8 (1.6–2.1) 54 (17.6) 224 (73.2) D22 Melanocytic naevi 97 3.8 1.8 (1.4–2.3) 25 (25.8) 57 (58.8) L57.0 Actinic keratosis 173 6.7 1.8 (1.5–2.1) 44 (25.4) 114 (65.9) D64 Other anaemias 197 7.7 1.8 (1.5–2.1) 28 (14.2) 149 (75.6) 2262 451 1604 aRows with grey shading indicate >75% of patients were registered with this code for the first time at the fourth or later consultation. Rows that are white indicate <75% of patients were registered with this code for the first time at the fourth or later consultation. bVisit 1 + 2 = the first two consultations. View Large Table 2 First time registered diagnostic codes (P-value < 0.01), their prevalence in cases, probability expressed in LR and relation to order of consultation Diagnostic codes ICD-10a Diagnostic codes, N Prev. >1% LR (95% CI) Visit 1 + 2b, n (%) Visit ≥4, n (%) N63 Lump in breast 101 3.9 11.9 (8.0–17.8) 5 (4.9) 95 (94.1) R77 Other abnormalities of plasma proteins 37 1.4 5.0 (3.0–8.2) 9 (24.3) 25 (67.6) R74 Abnormal serum enzyme levels 138 5.4 4.6 (3.6–5.9) 36 (26.0) 88 (63.8) R19.0 Intra-abdominal and pelvic swelling, mass and lump 30 1.2 4.4 (2.6–7.5] 0 28 (93.3) L85 Other epidermal thickening 32 1.2 4.3 (2.6–7.2] 3 (9.4) 27 (84.4) R19.4 Change in bowel habit 55 2.1 3.7 (2.5–5.3) 10 (18.2) 39 (70.9) N95.0 Postmenopausal bleeding 64 2.5 3.7 (2.6–5.2] 8 (12.5) 50 (78.1) K92.2 Gastrointestinal haemorrhage 28 1.1 3.5 (2.1–5.9) 2 (7.1) 22 (78.6) K62.5 Rectal bleeding 28 1.1 3.5 (2.1–5.9) 3 (10.7) 23 (82.1) K92.1 Melaena 40 1.6 3.5 (2.3–5.4) 5 (12.5) 30 (75.0) K92 Other diseases of digestive system 30 1.2 3.1 (1.9–5.1) 8 (26.7) 20 (66.7) R79 Other abnormal findings of blood chemistry 48 1.9 2.7 (1.9–3.9) 6 (12.5) 37 (77.1) K62 Other diseases of anus and rectum 84 3.3 2.7 (2.0–3.5) 11 (13.1) 67 (79.8) D12 Benign neoplasm of colon, rectum, anus and anal canal 38 1.5 2.7 (1.8–4.1) 5 (13.2) 29 (76.3) N83 Non-inflammatory disorders of ovary, fallopian tube and broad ligament 33 1.3 2.6 (1.7–4.1) 5 (15.2) 23 (69.7) D50 Iron deficiency anaemia 105 4.1 2.6 (2.0–3.3) 22 (20.9) 74 (70.5) R33 Retention of urine 95 3.7 2.4 (1.8–3.0) 25 (26.3) 58 (61.0) N42 Other disorders of prostate 101 3.9 2.3 (1.8–3.0) 28 (27.7) 66 (65.3) R31 Haematuria 71 2.7 2.2 (1.6–3.0) 17 (23.9) 46 (64.8) N40 Hyperplasia of prostate 331 12.9 2.0 (1.8–2.3) 92 (27.8) 213 (64.3) R23 Other skin changes 306 11.9 1.8 (1.6–2.1) 54 (17.6) 224 (73.2) D22 Melanocytic naevi 97 3.8 1.8 (1.4–2.3) 25 (25.8) 57 (58.8) L57.0 Actinic keratosis 173 6.7 1.8 (1.5–2.1) 44 (25.4) 114 (65.9) D64 Other anaemias 197 7.7 1.8 (1.5–2.1) 28 (14.2) 149 (75.6) 2262 451 1604 Diagnostic codes ICD-10a Diagnostic codes, N Prev. >1% LR (95% CI) Visit 1 + 2b, n (%) Visit ≥4, n (%) N63 Lump in breast 101 3.9 11.9 (8.0–17.8) 5 (4.9) 95 (94.1) R77 Other abnormalities of plasma proteins 37 1.4 5.0 (3.0–8.2) 9 (24.3) 25 (67.6) R74 Abnormal serum enzyme levels 138 5.4 4.6 (3.6–5.9) 36 (26.0) 88 (63.8) R19.0 Intra-abdominal and pelvic swelling, mass and lump 30 1.2 4.4 (2.6–7.5] 0 28 (93.3) L85 Other epidermal thickening 32 1.2 4.3 (2.6–7.2] 3 (9.4) 27 (84.4) R19.4 Change in bowel habit 55 2.1 3.7 (2.5–5.3) 10 (18.2) 39 (70.9) N95.0 Postmenopausal bleeding 64 2.5 3.7 (2.6–5.2] 8 (12.5) 50 (78.1) K92.2 Gastrointestinal haemorrhage 28 1.1 3.5 (2.1–5.9) 2 (7.1) 22 (78.6) K62.5 Rectal bleeding 28 1.1 3.5 (2.1–5.9) 3 (10.7) 23 (82.1) K92.1 Melaena 40 1.6 3.5 (2.3–5.4) 5 (12.5) 30 (75.0) K92 Other diseases of digestive system 30 1.2 3.1 (1.9–5.1) 8 (26.7) 20 (66.7) R79 Other abnormal findings of blood chemistry 48 1.9 2.7 (1.9–3.9) 6 (12.5) 37 (77.1) K62 Other diseases of anus and rectum 84 3.3 2.7 (2.0–3.5) 11 (13.1) 67 (79.8) D12 Benign neoplasm of colon, rectum, anus and anal canal 38 1.5 2.7 (1.8–4.1) 5 (13.2) 29 (76.3) N83 Non-inflammatory disorders of ovary, fallopian tube and broad ligament 33 1.3 2.6 (1.7–4.1) 5 (15.2) 23 (69.7) D50 Iron deficiency anaemia 105 4.1 2.6 (2.0–3.3) 22 (20.9) 74 (70.5) R33 Retention of urine 95 3.7 2.4 (1.8–3.0) 25 (26.3) 58 (61.0) N42 Other disorders of prostate 101 3.9 2.3 (1.8–3.0) 28 (27.7) 66 (65.3) R31 Haematuria 71 2.7 2.2 (1.6–3.0) 17 (23.9) 46 (64.8) N40 Hyperplasia of prostate 331 12.9 2.0 (1.8–2.3) 92 (27.8) 213 (64.3) R23 Other skin changes 306 11.9 1.8 (1.6–2.1) 54 (17.6) 224 (73.2) D22 Melanocytic naevi 97 3.8 1.8 (1.4–2.3) 25 (25.8) 57 (58.8) L57.0 Actinic keratosis 173 6.7 1.8 (1.5–2.1) 44 (25.4) 114 (65.9) D64 Other anaemias 197 7.7 1.8 (1.5–2.1) 28 (14.2) 149 (75.6) 2262 451 1604 aRows with grey shading indicate >75% of patients were registered with this code for the first time at the fourth or later consultation. Rows that are white indicate <75% of patients were registered with this code for the first time at the fourth or later consultation. bVisit 1 + 2 = the first two consultations. View Large Late clinical features where more than 75% were first presented at a fourth or later GP consultation were predominantly alarm symptoms such as lump in breast and rectal bleeding. Early clinical features where less than 75% were first presented at the fourth consultation but 14%–28% had been registered at the two first GP encounters were mostly features not known to be associated with cancer or were low-risk-but-not-no-risk symptoms of cancer. These early clinical features with the highest LR were attributed to abnormal blood tests, change in bowel habit, diseases of the digestive system, symptoms from the prostate and bladder and skin lesions (Table 2) (32). Of the statistically significant diagnostic codes associated with cancer, 17% or one out of six (375/2262) were early clinical features registered at the first two GP consultations. The relation of the clinical features to the different cancers showed that a lump in breast had the strongest association with breast cancer, abnormal serum enzyme levels with prostate cancer, iron deficiency anaemia with colorectal cancer, melanocytic naevi with malignant melanoma and postmenopausal bleeding with gynaecological cancer (Table 3). Table 3 Most frequent diagnostic codes related to cancer types Diagnostic codes ICD-10* LR (95% CI) Prostate, n = (%) Breast, n = (%) Skin, n = (%) MMa, n = (%) Lung, n = (%) Gynb, n = (%) CRCc, n = (%) Total, n = (%) N40 Hyperplasia of prostate 2.0 (1.8–2.3) 242 (73.1) 1 (0.3) 26 (7.9) 12 (3.6) 12 (3.6) 0 38 (11.4) 331 R23 Other skin changes 1.8 (1.6–2.1) 40 (13.1) 29 (9.5) 102 (33.3) 85 (27.8) 13 (4.2) 9 (2.9) 28 (9.2) 306 D64 Other anaemias 1.8 (1.5–2.1) 22 (11.2) 18 (9.1) 23 (11.7) 7 (7.2) 10 (5.1) 15 (7.6) 102 (51.8) 197 L57.0 Actinic keratosis 1.8 (1.5–2.1) 30 (18.5) 12 (6.9) 77 (44.5) 20 (11.6) 9 (5.2) 5 (2.9) 20 (11.6) 173 R74 Abnormal serum enzyme levels 4.6 (3.6–5.9) 120 (86.9) 0 2 (1.4) 2 (1.4) 4 (2.9) 0 10 (7.2) 138 D50 Iron deficiency anaemia 2.6 (2.0–3.3) 5 (4.8) 9 (8.6) 7 (6.7) 1 (1.0) 2 (1.9) 6 (5.7) 75 (71.4) 105 N63 Unspecified lump in breast 11.9 (8.0–17.8) 0 97 (96.0) 0 1 (1.0) 0 1 (1.0) 2 (2.0) 101 N42 Other disorder of prostate 2.3 (1.8–3.0) 80 (79.2) 0 2 (2.0) 4 (4.0) 7 (6.7) 0 8 (7.6) 101 D22 Melanocytic naevi 1.8 (1.4–2.3) 25 (25.8) 10 (10.3) 6 (6.2) 41 (42.3) 3 (3.1) 4 (4.1) 8 (8.2) 97 R33 Retention of urine 2.4 (1.8–3.0) 70 (73.7) 1 (1.0) 6 (6.3) 2 (2.1) 2 (2.1) 2 (2.1) 12 (12.6) 95 K62 Other diseases of colon and rectum 2.7 (2.0–3.5) 9 (10.7) 5 (6.0) 6 (7.1) 1 (1.2) 5 (6.0) 3 (3.6) 55 (65.5) 84 R31 Unspecified haematuria 2.2 (1.6–3.0) 40 (56.3) 5 (7.0) 4 (5.6) 3 (4.2) 4 (7.0) 7 (9.9) 8 (11.3) 71 N95.0 Postmenopausal bleeding 3.7 (2.6–5.2) 0 5 (7.8) 1 (1.6) 0 1 (1.6) 54 (84.4) 3 (4.7) 64 R19.4 Change in bowel habit 3.7 (2.5–5.3) 7 (12.7) 2 (3.6) 4 (7.3) 3 (5.4) 4 (7.3) 1 (1.8) 34 (61.8) 55 1918 Diagnostic codes ICD-10* LR (95% CI) Prostate, n = (%) Breast, n = (%) Skin, n = (%) MMa, n = (%) Lung, n = (%) Gynb, n = (%) CRCc, n = (%) Total, n = (%) N40 Hyperplasia of prostate 2.0 (1.8–2.3) 242 (73.1) 1 (0.3) 26 (7.9) 12 (3.6) 12 (3.6) 0 38 (11.4) 331 R23 Other skin changes 1.8 (1.6–2.1) 40 (13.1) 29 (9.5) 102 (33.3) 85 (27.8) 13 (4.2) 9 (2.9) 28 (9.2) 306 D64 Other anaemias 1.8 (1.5–2.1) 22 (11.2) 18 (9.1) 23 (11.7) 7 (7.2) 10 (5.1) 15 (7.6) 102 (51.8) 197 L57.0 Actinic keratosis 1.8 (1.5–2.1) 30 (18.5) 12 (6.9) 77 (44.5) 20 (11.6) 9 (5.2) 5 (2.9) 20 (11.6) 173 R74 Abnormal serum enzyme levels 4.6 (3.6–5.9) 120 (86.9) 0 2 (1.4) 2 (1.4) 4 (2.9) 0 10 (7.2) 138 D50 Iron deficiency anaemia 2.6 (2.0–3.3) 5 (4.8) 9 (8.6) 7 (6.7) 1 (1.0) 2 (1.9) 6 (5.7) 75 (71.4) 105 N63 Unspecified lump in breast 11.9 (8.0–17.8) 0 97 (96.0) 0 1 (1.0) 0 1 (1.0) 2 (2.0) 101 N42 Other disorder of prostate 2.3 (1.8–3.0) 80 (79.2) 0 2 (2.0) 4 (4.0) 7 (6.7) 0 8 (7.6) 101 D22 Melanocytic naevi 1.8 (1.4–2.3) 25 (25.8) 10 (10.3) 6 (6.2) 41 (42.3) 3 (3.1) 4 (4.1) 8 (8.2) 97 R33 Retention of urine 2.4 (1.8–3.0) 70 (73.7) 1 (1.0) 6 (6.3) 2 (2.1) 2 (2.1) 2 (2.1) 12 (12.6) 95 K62 Other diseases of colon and rectum 2.7 (2.0–3.5) 9 (10.7) 5 (6.0) 6 (7.1) 1 (1.2) 5 (6.0) 3 (3.6) 55 (65.5) 84 R31 Unspecified haematuria 2.2 (1.6–3.0) 40 (56.3) 5 (7.0) 4 (5.6) 3 (4.2) 4 (7.0) 7 (9.9) 8 (11.3) 71 N95.0 Postmenopausal bleeding 3.7 (2.6–5.2) 0 5 (7.8) 1 (1.6) 0 1 (1.6) 54 (84.4) 3 (4.7) 64 R19.4 Change in bowel habit 3.7 (2.5–5.3) 7 (12.7) 2 (3.6) 4 (7.3) 3 (5.4) 4 (7.3) 1 (1.8) 34 (61.8) 55 1918 LR, likelihood ratio calculated between cases and controls. aMalignant melanoma. bGynaecological cancer. cColorectal cancer. *P-value < 0.01. View Large Table 3 Most frequent diagnostic codes related to cancer types Diagnostic codes ICD-10* LR (95% CI) Prostate, n = (%) Breast, n = (%) Skin, n = (%) MMa, n = (%) Lung, n = (%) Gynb, n = (%) CRCc, n = (%) Total, n = (%) N40 Hyperplasia of prostate 2.0 (1.8–2.3) 242 (73.1) 1 (0.3) 26 (7.9) 12 (3.6) 12 (3.6) 0 38 (11.4) 331 R23 Other skin changes 1.8 (1.6–2.1) 40 (13.1) 29 (9.5) 102 (33.3) 85 (27.8) 13 (4.2) 9 (2.9) 28 (9.2) 306 D64 Other anaemias 1.8 (1.5–2.1) 22 (11.2) 18 (9.1) 23 (11.7) 7 (7.2) 10 (5.1) 15 (7.6) 102 (51.8) 197 L57.0 Actinic keratosis 1.8 (1.5–2.1) 30 (18.5) 12 (6.9) 77 (44.5) 20 (11.6) 9 (5.2) 5 (2.9) 20 (11.6) 173 R74 Abnormal serum enzyme levels 4.6 (3.6–5.9) 120 (86.9) 0 2 (1.4) 2 (1.4) 4 (2.9) 0 10 (7.2) 138 D50 Iron deficiency anaemia 2.6 (2.0–3.3) 5 (4.8) 9 (8.6) 7 (6.7) 1 (1.0) 2 (1.9) 6 (5.7) 75 (71.4) 105 N63 Unspecified lump in breast 11.9 (8.0–17.8) 0 97 (96.0) 0 1 (1.0) 0 1 (1.0) 2 (2.0) 101 N42 Other disorder of prostate 2.3 (1.8–3.0) 80 (79.2) 0 2 (2.0) 4 (4.0) 7 (6.7) 0 8 (7.6) 101 D22 Melanocytic naevi 1.8 (1.4–2.3) 25 (25.8) 10 (10.3) 6 (6.2) 41 (42.3) 3 (3.1) 4 (4.1) 8 (8.2) 97 R33 Retention of urine 2.4 (1.8–3.0) 70 (73.7) 1 (1.0) 6 (6.3) 2 (2.1) 2 (2.1) 2 (2.1) 12 (12.6) 95 K62 Other diseases of colon and rectum 2.7 (2.0–3.5) 9 (10.7) 5 (6.0) 6 (7.1) 1 (1.2) 5 (6.0) 3 (3.6) 55 (65.5) 84 R31 Unspecified haematuria 2.2 (1.6–3.0) 40 (56.3) 5 (7.0) 4 (5.6) 3 (4.2) 4 (7.0) 7 (9.9) 8 (11.3) 71 N95.0 Postmenopausal bleeding 3.7 (2.6–5.2) 0 5 (7.8) 1 (1.6) 0 1 (1.6) 54 (84.4) 3 (4.7) 64 R19.4 Change in bowel habit 3.7 (2.5–5.3) 7 (12.7) 2 (3.6) 4 (7.3) 3 (5.4) 4 (7.3) 1 (1.8) 34 (61.8) 55 1918 Diagnostic codes ICD-10* LR (95% CI) Prostate, n = (%) Breast, n = (%) Skin, n = (%) MMa, n = (%) Lung, n = (%) Gynb, n = (%) CRCc, n = (%) Total, n = (%) N40 Hyperplasia of prostate 2.0 (1.8–2.3) 242 (73.1) 1 (0.3) 26 (7.9) 12 (3.6) 12 (3.6) 0 38 (11.4) 331 R23 Other skin changes 1.8 (1.6–2.1) 40 (13.1) 29 (9.5) 102 (33.3) 85 (27.8) 13 (4.2) 9 (2.9) 28 (9.2) 306 D64 Other anaemias 1.8 (1.5–2.1) 22 (11.2) 18 (9.1) 23 (11.7) 7 (7.2) 10 (5.1) 15 (7.6) 102 (51.8) 197 L57.0 Actinic keratosis 1.8 (1.5–2.1) 30 (18.5) 12 (6.9) 77 (44.5) 20 (11.6) 9 (5.2) 5 (2.9) 20 (11.6) 173 R74 Abnormal serum enzyme levels 4.6 (3.6–5.9) 120 (86.9) 0 2 (1.4) 2 (1.4) 4 (2.9) 0 10 (7.2) 138 D50 Iron deficiency anaemia 2.6 (2.0–3.3) 5 (4.8) 9 (8.6) 7 (6.7) 1 (1.0) 2 (1.9) 6 (5.7) 75 (71.4) 105 N63 Unspecified lump in breast 11.9 (8.0–17.8) 0 97 (96.0) 0 1 (1.0) 0 1 (1.0) 2 (2.0) 101 N42 Other disorder of prostate 2.3 (1.8–3.0) 80 (79.2) 0 2 (2.0) 4 (4.0) 7 (6.7) 0 8 (7.6) 101 D22 Melanocytic naevi 1.8 (1.4–2.3) 25 (25.8) 10 (10.3) 6 (6.2) 41 (42.3) 3 (3.1) 4 (4.1) 8 (8.2) 97 R33 Retention of urine 2.4 (1.8–3.0) 70 (73.7) 1 (1.0) 6 (6.3) 2 (2.1) 2 (2.1) 2 (2.1) 12 (12.6) 95 K62 Other diseases of colon and rectum 2.7 (2.0–3.5) 9 (10.7) 5 (6.0) 6 (7.1) 1 (1.2) 5 (6.0) 3 (3.6) 55 (65.5) 84 R31 Unspecified haematuria 2.2 (1.6–3.0) 40 (56.3) 5 (7.0) 4 (5.6) 3 (4.2) 4 (7.0) 7 (9.9) 8 (11.3) 71 N95.0 Postmenopausal bleeding 3.7 (2.6–5.2) 0 5 (7.8) 1 (1.6) 0 1 (1.6) 54 (84.4) 3 (4.7) 64 R19.4 Change in bowel habit 3.7 (2.5–5.3) 7 (12.7) 2 (3.6) 4 (7.3) 3 (5.4) 4 (7.3) 1 (1.8) 34 (61.8) 55 1918 LR, likelihood ratio calculated between cases and controls. aMalignant melanoma. bGynaecological cancer. cColorectal cancer. *P-value < 0.01. View Large Discussion In the study, more than half of all the adult patients with the seven most common cancers had consulted a GP four times or more frequently in the year before cancer diagnosis. The majority of the clinical features associated with cancer had been registered at the fourth or a later consultation. Six out of ten features with the highest LR were alarm symptoms for cancer. However, 17% of the total number of codes had already been registered during the first two GP consultations, and these early clinical features were both alarm symptoms and features with more benign characteristics such as abnormal blood test, change in bowel habit, symptoms from the bladder and prostate and different skin lesions. Another two or more GP consultations were needed before the cancer was diagnosed. To our knowledge, this is the first study to provide information on when the different clinical features were presented at a GP consultation. A major finding of this study was that the majority of cancer patients consulted a GP at least four times before their cancer was diagnosed. This is in contrast with a UK study of national audit data on patients with 18 common and rarer cancers where 18% of the patients with symptoms that were relevant to cancer had three or more consultations (33). Comparing different studies on pre-referral consultations in primary care before cancer diagnosis can be confusing, as some relate to all consultations and others only to those with well-known cancer-related symptoms. A study presenting results concordant with ours reported that when any reason for consultation was considered (as in this study), about three-quarters of colorectal cancer patients had four or more pre-referral consultations in primary care (34). A large UK study from 2012 that was based on a national patient survey reported that 7% of patients with breast cancer and 10% of melanoma patients had three or more pre-referral consultations in primary care before a hospital referral to diagnose cancer (15). The symptoms relevant to the different cancers were defined by the patients. This perspective may, however, result in lost information of earlier unknown features that precede cancer diagnosis. Our study that was based on data collected from reliable databases and did not include any preconceived cancer symptoms showed a different result: 48% of breast cancer patients and 52% of malignant melanoma patients had four or more consultations in primary care before diagnosis (Table 1). Even though we did not have access to electronic medical records with information on when patients consulted for a suspected breast cancer symptom, 94% of all breast cancer patients received the diagnostic code unspecified lump in breast in primary care at the fourth or later consultation (Table 2). This makes us believe that the previous consultations were for other reasons than suspected breast cancer and that once the lump was registered, the patient was swiftly referred to secondary care for diagnosis. A Danish study that compared the patterns of general practice utilization in the period before lung cancer diagnosis reported that more than 72% of the patients had five or more consultations in the 12 months before the diagnosis (35). Face-to-face consultations, home visits and daytime phone calls were defined as consultations. This high proportion of patients with frequent consultations is in line with the findings in our study in which almost 66% of lung cancer patients consulted a GP four or more times in the year before cancer diagnosis. Another Danish study, which studied diagnostic activity in general practice during the year preceding colorectal cancer diagnosis, found that almost 50% of colorectal cancer patients had five or more consultations (36). This is comparable with our study in which more than 65% of patients that were later diagnosed with colorectal cancer consulted a GP four times or more. In our study, lump in breast has a strong association with breast cancer, which also has been shown in a UK study where breast lump was the feature with highest significant risk of breast cancer in symptomatic women in primary care (37). The findings from this study that are of particular interest relate to the early clinical features that were associated with cancer (Table 2). An abnormal serum enzyme level can mean a number of different enzymes such as transaminase but also elevated PSA, which is the main diagnostic pathway today for prostate cancer diagnosis. Change in bowel habit is a clinical feature that especially in younger individuals can be interpreted as a benign symptom. Nevertheless, it is considered being a low-risk-but-not-no-risk symptom of cancer, but especially if combined with rectal bleeding, also belongs to symptoms with an increased risk of colorectal cancer (38–41). Thus, the presence of a significant number of these clinical features during the first two consultations could signal missed diagnostic opportunities and therefore doctors’ delay. As this study is based on codes from a health care database and did not have access to medical records with the reasons for consultations, we do not know whether a patient with more than four consultations before a cancer diagnosis was consulting all four times because of cancer-associated symptoms. Nevertheless, when the patients consulted the GP with early clinical features and had to revisit their GP another two or three times before a diagnosis, one might ask why. Our study depicts in total four main reasons why a patient with a common cancer is not identified after the first or second GP consultation. The first reason is due to a GP not considering certain symptoms and signs quickly enough as potential cancer symptoms, for example, abnormal serum enzymes and/or plasma protein levels and a change in bowel habits (42). The second reason is due to the GP acknowledging a symptom or sign as alarming, but because medical investigation is time consuming, needing at least two more consultations before the final examination that diagnoses cancer. Iron deficiency anaemia, which needs a bowel exam before a colorectal cancer is diagnosed, is such an example. The third reason is that the patients’ symptoms suggested a benign disease of the prostate, digestive system or skin, and the GP used the watchful-waiting tool (43). An interesting observation is that codes for symptoms and diseases of the respiratory system were absent in our study sample even though lung cancer patients were included. This could explain why it is so hard to suspect lung cancer early, with the consequences being late diagnosis (44). The fourth reason is simply due to cancer patients with comorbid conditions consulting for other medical problems than those emanating from cancer in the year before cancer diagnosis. One of the key messages in this study is that an un-neglectable proportion of patients that had presented with early clinical features at the first two GP consultations were not swiftly acted upon by the GPs. Thus, these consultations represented missed diagnostic opportunities and therefore delayed cancer diagnosis, which has also been acknowledged in other studies (21,45). The literature reports that 40%–50% of the patients that consult a GP and are later diagnosed with cancer present with alarm symptoms (46,47). This study confirms the figures on alarm symptoms in patients with frequent consultations but differs in the sense that more than half of the patients that had early clinical features associated with cancer did not present with diffuse symptomatology such as pain or fatigue but with focal features with benign characteristics. A strength of our study is that it is based on a total population. All the adult patients with the seven most common cancers in a large region in Sweden were included. Another strength is the use of reliable regional and national databases with almost complete coverage of cancer diagnoses and diagnostic codes from primary care. As the diagnostic codes were registered before the cancer diagnosis and were automatically retrieved, selection bias has been avoided. As it is mandatory for Swedish GPs to code because of the reimbursement system, an extensive and reliable amount of data are available. All diagnostic codes have been collected, not just those preconceived as being well-known symptoms of cancer. One limitation of the study is that the coded information from the health care databases might not have captured all the symptoms and the clinical features presented by the patients and registered in the electronic medical record (48). This has been observed in other fields of research in primary care databases, such as that of rheumatoid arthritis (44). The time span used in our study may also be a limitation. Even though many studies suggest that most cancer symptoms occur 3–6 months before a cancer diagnosis (18,36,49), a longer time span might be needed. Another limitation is that the data analysis was done in a sample with an uneven number of the different cancers. As patients with prostate, colorectal and breast cancer represented 62% of the seven cancers in this study, the diagnostic codes from these patients have probably resulted in a higher LR, than if all the cancers were equally represented. A weakness of our study is that no respiratory symptoms associated with lung cancer were found, which could depend on either an underregistration of these symptoms by the GPs, or lung cancer patients being too few (10%) in proportion to all the other cancers in our study. Conclusion More than half of the patients with common cancers had consulted a GP at least four times in the year before their cancer diagnosis. One out of six clinical features that they presented already at the two first consultations were focal and had benign characteristics. These features might have been missed diagnostic opportunities. A more vigilant approach towards patients presenting in primary care with these clinical features could result in timelier cancer diagnoses. Acknowledgements The authors thank Erik Holmberg PhD, statistician at Regional Cancer Centre West for the extraction of data from the SCR. We also thank Kristina Narbro PhD and Mona–Lis Dalbrekt, Department of Health Care Evaluation, County Council, Västra Götaland Region, for help in the extraction of data from the regional health care database. Declaration Funding: The study was conducted without external funding. 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Br J Cancer 2015 ; 112 : 271 – 7 . Google Scholar Crossref Search ADS PubMed © The Author(s) 2018. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model) http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Family Practice Oxford University Press

Diagnostic profile characteristics of cancer patients with frequent consultations in primary care before diagnosis: a case-control study

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Oxford University Press
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© The Author(s) 2018. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
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0263-2136
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1460-2229
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10.1093/fampra/cmy012
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Abstract

Abstract Background Many patients with common cancers are late diagnosed. Objectives Identify consultation profiles and clinical features in patients with the seven most common cancers, who had consulted a general practitioner (GP) frequently before their cancer diagnosis. Methods A case-control study was conducted in Region Västra Götaland, Sweden. A total of 2570 patients, diagnosed in 2011 with prostate, breast, colorectal, lung, gynaecological and skin cancers including malignant melanoma, and 9424 controls were selected from the Swedish Cancer Register and a regional health care database. Diagnostic codes [International Statistical Classification of Diseases and Related Health Problems, 10th revision (ICD-10)] from primary care for patients with ≥4 GP consultations registered in the year before cancer diagnosis were collected. Likelihood ratios (LRs) were calculated for variables associated with the different cancers. Results Fifty-six percent of the patients had consulted a GP four or more times in the year before cancer diagnosis. Alarm symptoms or signs represented 60% of the codes with the highest LR, but only 40% of the 10 most prevalent codes. Breast lump had the highest LR, 11.9 [95% confidence interval (CI) 8.0–17.8]; abnormalities of plasma proteins had an LR of 5.0 (95% CI 3.0–8.2) and abnormal serum enzyme levels had an LR of 4.6 (95% CI 3.6–5.9). Early clinical features associated with cancer had been registered already at the first two GP consultations. Conclusion One out of six clinical features associated with cancer were presented by cancer patients with four or more pre-referral consultations already at the two first consultations. These early clinical features that were focal and had benign characteristics might have been missed diagnostic opportunities. Cancer, consultation, diagnosis, general practice, ICD codes, primary health care Introduction Despite great advances in diagnostics and the treatment of cancer, many of the most common cancers are diagnosed at an advanced stage. There has been a lack of consensus over whether a delay in cancer diagnosis truly affects survival (1–3). However, there is growing evidence that screening and early detection of symptomatic cancer results in a better prognosis for the patient (4–11). Our knowledge about clinical features of different cancers has, until quite recently, come from research in secondary care. Yet, more than two-thirds of all cancers are diagnosed in primary care (8,12–16). An increased consultation rate in primary care before a cancer diagnosis has been reported in the literature (17–21). Not only the clinical benefit of timely cancer diagnosis but also patient preferences and patient experience have to be considered. There is now evidence of a negative association between multiple pre-diagnostic consultations with a general practitioner (GP) and the experience of subsequent cancer care (22). The challenge for the GP is to identify the relatively few cancer patients among the many patients who present with symptoms and clinical features that are mostly the same for benign and for malignant diseases. Alarm symptoms are clinical features that are considered to predict serious, often malignant disease, for example, unexplained lump in breast for breast cancer and rectal bleeding for colorectal cancer. The majority of urgent referral pathways for cancer that are now implemented in the UK and several Scandinavian countries are based on the presentation of these features. In the UK, features with a positive predictive value (PPV) of 3% or higher that are defined in the NICE guidelines warrant urgent referral and appointment within 2 weeks (4,23). Cancer can also present with vague, unspecific symptoms that have unspecific origin (14,24). However, even when features are focal, derived from a specific organ and having the characteristics of a benign condition, the underlying cause can be that of cancer (21). Sweden is well known for its total population databases, which is why a case-control study was conducted using the regional database for health care and the National Cancer Register. This study aimed to identify the diagnostic profiles including potential missed diagnostic opportunities both in relation to the sequence of consultations and cancer type, in cancer patients with four or more GP consultations in the year before cancer diagnosis. Methods Study design A population-based case-control study was designed using the Swedish Cancer Register (SCR) and a regional health care database in Region Västra Götaland (RVG), Sweden. This region, which has 1.6 million inhabitants (17% of the Swedish population), is situated in the south-west of Sweden and includes rural and urban areas. The SCR, which was established in 1958, is one of the oldest disease registers in the world and has high validity (25). All physicians, including pathologists, in Sweden are obliged by law to report all incident cases of cancer from both living and dead patients to the SCR (26). Each patient has a unique personal identity number that all Swedish residents acquire either at birth or when they immigrate to Sweden. The regional health care database was established in RVG in 2000. It covers all hospitals, specialized outpatient care and all private and public primary health care centres. The database includes the patient’s Swedish personal identity number, place of residence, age, sex, health care contacts and diagnostic codes for diagnoses and surgical procedures (27). At each consultation, physicians are obliged to enter the codes for a patient’s current disease(s) or symptoms into the patient’s medical records. The reimbursement system for primary care providers is partly based on the disease burden of the patients, which is defined by diagnostic codes reported to this database. Study population Cases eligible for the study were identified from the SCR for the period 1 January 2011 to 31 December 2011. Inclusion criteria were as follows: diagnosed in RVG with one of the seven most common cancers—prostate cancer, breast cancer, colorectal cancer, lung cancer, gynaecological cancer or skin cancers, including malignant melanoma; alive at the time of the cancer diagnosis; aged ≥18 years and consulted a GP four or more times during the year before cancer diagnosis. Individuals were excluded from participation if they lacked a control and had a previous cancer diagnosis in the SCR (1991–2010). The patients with an earlier cancer diagnosis were deliberately omitted to avoid consultations in primary care being a control or concern of a previous cancer. Controls were selected from the regional health care database. They had the same inclusion criteria as the patients with cancer, with the exception of the cancer diagnosis. Four controls were matched to each case on age, sex and primary care unit. Matching of patients and controls had to be done before retrieving data regarding diagnostic codes and consultation dates from the regional health care database. A final selection of patients and controls with four or more consultations was then made, and therefore, not all patients retained four controls. Data collection The unique personal identity numbers of both cases and controls were linked to the regional health care database. All data concerning diagnoses and dates of consultations with a GP between 1 January 2010 and 31 December 2011 were collected. For the cases, only diagnostic codes before the date of their cancer diagnosis were collected. The data extracted included diagnostic codes according to the following: Swedish version of the International Statistical Classification of Diseases and Related Health Problems, 10th revision (ICD-10) or Classification of Diseases and Health Problems 1997 Primary Care (KSH97-P)—this is an abbreviated version of ICD-10, adapted to Swedish primary care to facilitate diagnostic coding (28–30). Diagnostic codes All the diagnostic codes registered when the cases and their controls consulted a GP during the study period were studied. As more than 6000 different diagnostic codes were received, their number was reduced by merging the four-character diagnostic codes to the closest three-character diagnostic codes according to clinical relevance (19). This was done because the incidence of the individual ICD-10 codes was too low to conduct statistical analyses. Finally, 575 codes remained that occurred in ≥1% of either cases or controls. The codes represented both diseases, symptoms and clinical findings such as laboratory results, and so henceforth they will be referred to as clinical features. Data analyses The 575 diagnostic codes were then used for univariable conditional logistic regression at significance level 0.01. Those diagnostic codes found to be associated with cancer were then analysed to see to which cancer they were associated. The likelihood ratio (LR) was then calculated. LR is a measure that expresses the probability of any clinical finding in patients with a disorder divided by the probability of the same finding in patients without the disorder (31). The LR was computed for all seven cancers combined as the study aimed to reflect the whole panorama of different symptoms/features of the most common cancers presented to the GPs. After this procedure, the codes were sorted in consultation order and organized into two groups: ‘early clinical features’ where a great proportion of them had been registered at the two first consultations and less than 75% after the fourth or a later consultation and ‘late clinical features’ where more than 75% were first presented at the fourth or a later GP consultation. All analyses were performed using the statistical software R (version 3.0.1). Results Cases and controls As the flowchart of the study sample recruitment process shows (Fig. 1), 2570 cancer patients fulfilled all inclusion and exclusion criteria. Because 269 controls died before their cases were diagnosed with cancer and 587 did not have four or more visits in primary care, there were not always four controls for each case. This resulted in 9424 controls in the final sample. Characteristics of the sample are outlined in Table 1. Of the patients with the seven most common cancers in this study, who had consulted a GP in the year prior to cancer diagnosis, 56% had four or more face-to-face consultations (Fig. 1). Figure 1 View largeDownload slide Sample recruitment flowchart Figure 1 View largeDownload slide Sample recruitment flowchart Table 1 Cancer patients that consulted primary care four or more times the year prior to cancer diagnosis Characteristics Cancer patients ≥4 consultations, n = 2570 (%) Controls ≥4 consultations, n = 9424 (%) Proportion of the individual cancers in the total cancer sample with no regard to no. of consultations, n = 4562 (%) Prostate cancer 637 (25) 2443 (51) Breast cancer 456 (18) 2028 (48) Colorectal cancer 493 (19) 1600 (65) Lung cancer 245 (10) 799 (66) Malignant melanoma 240 (9) 886 (52) Skin cancer 294 (11) 950 (66) Gynaecological cancer 205 (8) 718 (63) Female 1337 (52) 5020 (53) Male 1233 (48) 4404 (47) Median age at diagnosis, years (range) 71 (29–97) 70 (29–97) <60 years 491 (19) 1967 (21) 60–80 years 1553(60) 5769 (61) >80 years 526 (20) 1688 (18) Median number of consultations per patient in year before cancer diagnosis, n (IQR) 7 (5–10) 7 (5–10) Median number of unique diagnostic codes per patient in year before cancer diagnosis, n (IQR) 8 (5–11) 8 (6–11) Characteristics Cancer patients ≥4 consultations, n = 2570 (%) Controls ≥4 consultations, n = 9424 (%) Proportion of the individual cancers in the total cancer sample with no regard to no. of consultations, n = 4562 (%) Prostate cancer 637 (25) 2443 (51) Breast cancer 456 (18) 2028 (48) Colorectal cancer 493 (19) 1600 (65) Lung cancer 245 (10) 799 (66) Malignant melanoma 240 (9) 886 (52) Skin cancer 294 (11) 950 (66) Gynaecological cancer 205 (8) 718 (63) Female 1337 (52) 5020 (53) Male 1233 (48) 4404 (47) Median age at diagnosis, years (range) 71 (29–97) 70 (29–97) <60 years 491 (19) 1967 (21) 60–80 years 1553(60) 5769 (61) >80 years 526 (20) 1688 (18) Median number of consultations per patient in year before cancer diagnosis, n (IQR) 7 (5–10) 7 (5–10) Median number of unique diagnostic codes per patient in year before cancer diagnosis, n (IQR) 8 (5–11) 8 (6–11) IQR, interquartile range. View Large Table 1 Cancer patients that consulted primary care four or more times the year prior to cancer diagnosis Characteristics Cancer patients ≥4 consultations, n = 2570 (%) Controls ≥4 consultations, n = 9424 (%) Proportion of the individual cancers in the total cancer sample with no regard to no. of consultations, n = 4562 (%) Prostate cancer 637 (25) 2443 (51) Breast cancer 456 (18) 2028 (48) Colorectal cancer 493 (19) 1600 (65) Lung cancer 245 (10) 799 (66) Malignant melanoma 240 (9) 886 (52) Skin cancer 294 (11) 950 (66) Gynaecological cancer 205 (8) 718 (63) Female 1337 (52) 5020 (53) Male 1233 (48) 4404 (47) Median age at diagnosis, years (range) 71 (29–97) 70 (29–97) <60 years 491 (19) 1967 (21) 60–80 years 1553(60) 5769 (61) >80 years 526 (20) 1688 (18) Median number of consultations per patient in year before cancer diagnosis, n (IQR) 7 (5–10) 7 (5–10) Median number of unique diagnostic codes per patient in year before cancer diagnosis, n (IQR) 8 (5–11) 8 (6–11) Characteristics Cancer patients ≥4 consultations, n = 2570 (%) Controls ≥4 consultations, n = 9424 (%) Proportion of the individual cancers in the total cancer sample with no regard to no. of consultations, n = 4562 (%) Prostate cancer 637 (25) 2443 (51) Breast cancer 456 (18) 2028 (48) Colorectal cancer 493 (19) 1600 (65) Lung cancer 245 (10) 799 (66) Malignant melanoma 240 (9) 886 (52) Skin cancer 294 (11) 950 (66) Gynaecological cancer 205 (8) 718 (63) Female 1337 (52) 5020 (53) Male 1233 (48) 4404 (47) Median age at diagnosis, years (range) 71 (29–97) 70 (29–97) <60 years 491 (19) 1967 (21) 60–80 years 1553(60) 5769 (61) >80 years 526 (20) 1688 (18) Median number of consultations per patient in year before cancer diagnosis, n (IQR) 7 (5–10) 7 (5–10) Median number of unique diagnostic codes per patient in year before cancer diagnosis, n (IQR) 8 (5–11) 8 (6–11) IQR, interquartile range. View Large Diagnostic codes All 575 variables were used for univariate logistic regression, and this resulted in 34 statistically significant variables (P-value < 0.01) with LR higher than one. The diagnostic codes for neoplasm of uncertain or unknown behaviour, of female organs, oral cavity or digestive organs, and of carcinoma in situ of skin were removed from all cancer cases with no regard to cancer type because the study focused on clinical features present before the cancer diagnosis, and these codes more or less signalled the cancer diagnosis. After also removing the diagnostic code for ‘other medical care’, 26 remaining variables had a LR higher than 1.5, but only 24 had a prevalence higher than 1% and were retained (Table 2). Between 59% and 94% of the diagnostic codes were first registered at the patients’ fourth or later GP consultation. Six out of ten of the codes with the highest LR were alarm symptoms for cancer; however, when sorted for how prevalent they were in the cancer population, only 4 out of the 10 turned out to be alarm symptoms. Table 2 First time registered diagnostic codes (P-value < 0.01), their prevalence in cases, probability expressed in LR and relation to order of consultation Diagnostic codes ICD-10a Diagnostic codes, N Prev. >1% LR (95% CI) Visit 1 + 2b, n (%) Visit ≥4, n (%) N63 Lump in breast 101 3.9 11.9 (8.0–17.8) 5 (4.9) 95 (94.1) R77 Other abnormalities of plasma proteins 37 1.4 5.0 (3.0–8.2) 9 (24.3) 25 (67.6) R74 Abnormal serum enzyme levels 138 5.4 4.6 (3.6–5.9) 36 (26.0) 88 (63.8) R19.0 Intra-abdominal and pelvic swelling, mass and lump 30 1.2 4.4 (2.6–7.5] 0 28 (93.3) L85 Other epidermal thickening 32 1.2 4.3 (2.6–7.2] 3 (9.4) 27 (84.4) R19.4 Change in bowel habit 55 2.1 3.7 (2.5–5.3) 10 (18.2) 39 (70.9) N95.0 Postmenopausal bleeding 64 2.5 3.7 (2.6–5.2] 8 (12.5) 50 (78.1) K92.2 Gastrointestinal haemorrhage 28 1.1 3.5 (2.1–5.9) 2 (7.1) 22 (78.6) K62.5 Rectal bleeding 28 1.1 3.5 (2.1–5.9) 3 (10.7) 23 (82.1) K92.1 Melaena 40 1.6 3.5 (2.3–5.4) 5 (12.5) 30 (75.0) K92 Other diseases of digestive system 30 1.2 3.1 (1.9–5.1) 8 (26.7) 20 (66.7) R79 Other abnormal findings of blood chemistry 48 1.9 2.7 (1.9–3.9) 6 (12.5) 37 (77.1) K62 Other diseases of anus and rectum 84 3.3 2.7 (2.0–3.5) 11 (13.1) 67 (79.8) D12 Benign neoplasm of colon, rectum, anus and anal canal 38 1.5 2.7 (1.8–4.1) 5 (13.2) 29 (76.3) N83 Non-inflammatory disorders of ovary, fallopian tube and broad ligament 33 1.3 2.6 (1.7–4.1) 5 (15.2) 23 (69.7) D50 Iron deficiency anaemia 105 4.1 2.6 (2.0–3.3) 22 (20.9) 74 (70.5) R33 Retention of urine 95 3.7 2.4 (1.8–3.0) 25 (26.3) 58 (61.0) N42 Other disorders of prostate 101 3.9 2.3 (1.8–3.0) 28 (27.7) 66 (65.3) R31 Haematuria 71 2.7 2.2 (1.6–3.0) 17 (23.9) 46 (64.8) N40 Hyperplasia of prostate 331 12.9 2.0 (1.8–2.3) 92 (27.8) 213 (64.3) R23 Other skin changes 306 11.9 1.8 (1.6–2.1) 54 (17.6) 224 (73.2) D22 Melanocytic naevi 97 3.8 1.8 (1.4–2.3) 25 (25.8) 57 (58.8) L57.0 Actinic keratosis 173 6.7 1.8 (1.5–2.1) 44 (25.4) 114 (65.9) D64 Other anaemias 197 7.7 1.8 (1.5–2.1) 28 (14.2) 149 (75.6) 2262 451 1604 Diagnostic codes ICD-10a Diagnostic codes, N Prev. >1% LR (95% CI) Visit 1 + 2b, n (%) Visit ≥4, n (%) N63 Lump in breast 101 3.9 11.9 (8.0–17.8) 5 (4.9) 95 (94.1) R77 Other abnormalities of plasma proteins 37 1.4 5.0 (3.0–8.2) 9 (24.3) 25 (67.6) R74 Abnormal serum enzyme levels 138 5.4 4.6 (3.6–5.9) 36 (26.0) 88 (63.8) R19.0 Intra-abdominal and pelvic swelling, mass and lump 30 1.2 4.4 (2.6–7.5] 0 28 (93.3) L85 Other epidermal thickening 32 1.2 4.3 (2.6–7.2] 3 (9.4) 27 (84.4) R19.4 Change in bowel habit 55 2.1 3.7 (2.5–5.3) 10 (18.2) 39 (70.9) N95.0 Postmenopausal bleeding 64 2.5 3.7 (2.6–5.2] 8 (12.5) 50 (78.1) K92.2 Gastrointestinal haemorrhage 28 1.1 3.5 (2.1–5.9) 2 (7.1) 22 (78.6) K62.5 Rectal bleeding 28 1.1 3.5 (2.1–5.9) 3 (10.7) 23 (82.1) K92.1 Melaena 40 1.6 3.5 (2.3–5.4) 5 (12.5) 30 (75.0) K92 Other diseases of digestive system 30 1.2 3.1 (1.9–5.1) 8 (26.7) 20 (66.7) R79 Other abnormal findings of blood chemistry 48 1.9 2.7 (1.9–3.9) 6 (12.5) 37 (77.1) K62 Other diseases of anus and rectum 84 3.3 2.7 (2.0–3.5) 11 (13.1) 67 (79.8) D12 Benign neoplasm of colon, rectum, anus and anal canal 38 1.5 2.7 (1.8–4.1) 5 (13.2) 29 (76.3) N83 Non-inflammatory disorders of ovary, fallopian tube and broad ligament 33 1.3 2.6 (1.7–4.1) 5 (15.2) 23 (69.7) D50 Iron deficiency anaemia 105 4.1 2.6 (2.0–3.3) 22 (20.9) 74 (70.5) R33 Retention of urine 95 3.7 2.4 (1.8–3.0) 25 (26.3) 58 (61.0) N42 Other disorders of prostate 101 3.9 2.3 (1.8–3.0) 28 (27.7) 66 (65.3) R31 Haematuria 71 2.7 2.2 (1.6–3.0) 17 (23.9) 46 (64.8) N40 Hyperplasia of prostate 331 12.9 2.0 (1.8–2.3) 92 (27.8) 213 (64.3) R23 Other skin changes 306 11.9 1.8 (1.6–2.1) 54 (17.6) 224 (73.2) D22 Melanocytic naevi 97 3.8 1.8 (1.4–2.3) 25 (25.8) 57 (58.8) L57.0 Actinic keratosis 173 6.7 1.8 (1.5–2.1) 44 (25.4) 114 (65.9) D64 Other anaemias 197 7.7 1.8 (1.5–2.1) 28 (14.2) 149 (75.6) 2262 451 1604 aRows with grey shading indicate >75% of patients were registered with this code for the first time at the fourth or later consultation. Rows that are white indicate <75% of patients were registered with this code for the first time at the fourth or later consultation. bVisit 1 + 2 = the first two consultations. View Large Table 2 First time registered diagnostic codes (P-value < 0.01), their prevalence in cases, probability expressed in LR and relation to order of consultation Diagnostic codes ICD-10a Diagnostic codes, N Prev. >1% LR (95% CI) Visit 1 + 2b, n (%) Visit ≥4, n (%) N63 Lump in breast 101 3.9 11.9 (8.0–17.8) 5 (4.9) 95 (94.1) R77 Other abnormalities of plasma proteins 37 1.4 5.0 (3.0–8.2) 9 (24.3) 25 (67.6) R74 Abnormal serum enzyme levels 138 5.4 4.6 (3.6–5.9) 36 (26.0) 88 (63.8) R19.0 Intra-abdominal and pelvic swelling, mass and lump 30 1.2 4.4 (2.6–7.5] 0 28 (93.3) L85 Other epidermal thickening 32 1.2 4.3 (2.6–7.2] 3 (9.4) 27 (84.4) R19.4 Change in bowel habit 55 2.1 3.7 (2.5–5.3) 10 (18.2) 39 (70.9) N95.0 Postmenopausal bleeding 64 2.5 3.7 (2.6–5.2] 8 (12.5) 50 (78.1) K92.2 Gastrointestinal haemorrhage 28 1.1 3.5 (2.1–5.9) 2 (7.1) 22 (78.6) K62.5 Rectal bleeding 28 1.1 3.5 (2.1–5.9) 3 (10.7) 23 (82.1) K92.1 Melaena 40 1.6 3.5 (2.3–5.4) 5 (12.5) 30 (75.0) K92 Other diseases of digestive system 30 1.2 3.1 (1.9–5.1) 8 (26.7) 20 (66.7) R79 Other abnormal findings of blood chemistry 48 1.9 2.7 (1.9–3.9) 6 (12.5) 37 (77.1) K62 Other diseases of anus and rectum 84 3.3 2.7 (2.0–3.5) 11 (13.1) 67 (79.8) D12 Benign neoplasm of colon, rectum, anus and anal canal 38 1.5 2.7 (1.8–4.1) 5 (13.2) 29 (76.3) N83 Non-inflammatory disorders of ovary, fallopian tube and broad ligament 33 1.3 2.6 (1.7–4.1) 5 (15.2) 23 (69.7) D50 Iron deficiency anaemia 105 4.1 2.6 (2.0–3.3) 22 (20.9) 74 (70.5) R33 Retention of urine 95 3.7 2.4 (1.8–3.0) 25 (26.3) 58 (61.0) N42 Other disorders of prostate 101 3.9 2.3 (1.8–3.0) 28 (27.7) 66 (65.3) R31 Haematuria 71 2.7 2.2 (1.6–3.0) 17 (23.9) 46 (64.8) N40 Hyperplasia of prostate 331 12.9 2.0 (1.8–2.3) 92 (27.8) 213 (64.3) R23 Other skin changes 306 11.9 1.8 (1.6–2.1) 54 (17.6) 224 (73.2) D22 Melanocytic naevi 97 3.8 1.8 (1.4–2.3) 25 (25.8) 57 (58.8) L57.0 Actinic keratosis 173 6.7 1.8 (1.5–2.1) 44 (25.4) 114 (65.9) D64 Other anaemias 197 7.7 1.8 (1.5–2.1) 28 (14.2) 149 (75.6) 2262 451 1604 Diagnostic codes ICD-10a Diagnostic codes, N Prev. >1% LR (95% CI) Visit 1 + 2b, n (%) Visit ≥4, n (%) N63 Lump in breast 101 3.9 11.9 (8.0–17.8) 5 (4.9) 95 (94.1) R77 Other abnormalities of plasma proteins 37 1.4 5.0 (3.0–8.2) 9 (24.3) 25 (67.6) R74 Abnormal serum enzyme levels 138 5.4 4.6 (3.6–5.9) 36 (26.0) 88 (63.8) R19.0 Intra-abdominal and pelvic swelling, mass and lump 30 1.2 4.4 (2.6–7.5] 0 28 (93.3) L85 Other epidermal thickening 32 1.2 4.3 (2.6–7.2] 3 (9.4) 27 (84.4) R19.4 Change in bowel habit 55 2.1 3.7 (2.5–5.3) 10 (18.2) 39 (70.9) N95.0 Postmenopausal bleeding 64 2.5 3.7 (2.6–5.2] 8 (12.5) 50 (78.1) K92.2 Gastrointestinal haemorrhage 28 1.1 3.5 (2.1–5.9) 2 (7.1) 22 (78.6) K62.5 Rectal bleeding 28 1.1 3.5 (2.1–5.9) 3 (10.7) 23 (82.1) K92.1 Melaena 40 1.6 3.5 (2.3–5.4) 5 (12.5) 30 (75.0) K92 Other diseases of digestive system 30 1.2 3.1 (1.9–5.1) 8 (26.7) 20 (66.7) R79 Other abnormal findings of blood chemistry 48 1.9 2.7 (1.9–3.9) 6 (12.5) 37 (77.1) K62 Other diseases of anus and rectum 84 3.3 2.7 (2.0–3.5) 11 (13.1) 67 (79.8) D12 Benign neoplasm of colon, rectum, anus and anal canal 38 1.5 2.7 (1.8–4.1) 5 (13.2) 29 (76.3) N83 Non-inflammatory disorders of ovary, fallopian tube and broad ligament 33 1.3 2.6 (1.7–4.1) 5 (15.2) 23 (69.7) D50 Iron deficiency anaemia 105 4.1 2.6 (2.0–3.3) 22 (20.9) 74 (70.5) R33 Retention of urine 95 3.7 2.4 (1.8–3.0) 25 (26.3) 58 (61.0) N42 Other disorders of prostate 101 3.9 2.3 (1.8–3.0) 28 (27.7) 66 (65.3) R31 Haematuria 71 2.7 2.2 (1.6–3.0) 17 (23.9) 46 (64.8) N40 Hyperplasia of prostate 331 12.9 2.0 (1.8–2.3) 92 (27.8) 213 (64.3) R23 Other skin changes 306 11.9 1.8 (1.6–2.1) 54 (17.6) 224 (73.2) D22 Melanocytic naevi 97 3.8 1.8 (1.4–2.3) 25 (25.8) 57 (58.8) L57.0 Actinic keratosis 173 6.7 1.8 (1.5–2.1) 44 (25.4) 114 (65.9) D64 Other anaemias 197 7.7 1.8 (1.5–2.1) 28 (14.2) 149 (75.6) 2262 451 1604 aRows with grey shading indicate >75% of patients were registered with this code for the first time at the fourth or later consultation. Rows that are white indicate <75% of patients were registered with this code for the first time at the fourth or later consultation. bVisit 1 + 2 = the first two consultations. View Large Late clinical features where more than 75% were first presented at a fourth or later GP consultation were predominantly alarm symptoms such as lump in breast and rectal bleeding. Early clinical features where less than 75% were first presented at the fourth consultation but 14%–28% had been registered at the two first GP encounters were mostly features not known to be associated with cancer or were low-risk-but-not-no-risk symptoms of cancer. These early clinical features with the highest LR were attributed to abnormal blood tests, change in bowel habit, diseases of the digestive system, symptoms from the prostate and bladder and skin lesions (Table 2) (32). Of the statistically significant diagnostic codes associated with cancer, 17% or one out of six (375/2262) were early clinical features registered at the first two GP consultations. The relation of the clinical features to the different cancers showed that a lump in breast had the strongest association with breast cancer, abnormal serum enzyme levels with prostate cancer, iron deficiency anaemia with colorectal cancer, melanocytic naevi with malignant melanoma and postmenopausal bleeding with gynaecological cancer (Table 3). Table 3 Most frequent diagnostic codes related to cancer types Diagnostic codes ICD-10* LR (95% CI) Prostate, n = (%) Breast, n = (%) Skin, n = (%) MMa, n = (%) Lung, n = (%) Gynb, n = (%) CRCc, n = (%) Total, n = (%) N40 Hyperplasia of prostate 2.0 (1.8–2.3) 242 (73.1) 1 (0.3) 26 (7.9) 12 (3.6) 12 (3.6) 0 38 (11.4) 331 R23 Other skin changes 1.8 (1.6–2.1) 40 (13.1) 29 (9.5) 102 (33.3) 85 (27.8) 13 (4.2) 9 (2.9) 28 (9.2) 306 D64 Other anaemias 1.8 (1.5–2.1) 22 (11.2) 18 (9.1) 23 (11.7) 7 (7.2) 10 (5.1) 15 (7.6) 102 (51.8) 197 L57.0 Actinic keratosis 1.8 (1.5–2.1) 30 (18.5) 12 (6.9) 77 (44.5) 20 (11.6) 9 (5.2) 5 (2.9) 20 (11.6) 173 R74 Abnormal serum enzyme levels 4.6 (3.6–5.9) 120 (86.9) 0 2 (1.4) 2 (1.4) 4 (2.9) 0 10 (7.2) 138 D50 Iron deficiency anaemia 2.6 (2.0–3.3) 5 (4.8) 9 (8.6) 7 (6.7) 1 (1.0) 2 (1.9) 6 (5.7) 75 (71.4) 105 N63 Unspecified lump in breast 11.9 (8.0–17.8) 0 97 (96.0) 0 1 (1.0) 0 1 (1.0) 2 (2.0) 101 N42 Other disorder of prostate 2.3 (1.8–3.0) 80 (79.2) 0 2 (2.0) 4 (4.0) 7 (6.7) 0 8 (7.6) 101 D22 Melanocytic naevi 1.8 (1.4–2.3) 25 (25.8) 10 (10.3) 6 (6.2) 41 (42.3) 3 (3.1) 4 (4.1) 8 (8.2) 97 R33 Retention of urine 2.4 (1.8–3.0) 70 (73.7) 1 (1.0) 6 (6.3) 2 (2.1) 2 (2.1) 2 (2.1) 12 (12.6) 95 K62 Other diseases of colon and rectum 2.7 (2.0–3.5) 9 (10.7) 5 (6.0) 6 (7.1) 1 (1.2) 5 (6.0) 3 (3.6) 55 (65.5) 84 R31 Unspecified haematuria 2.2 (1.6–3.0) 40 (56.3) 5 (7.0) 4 (5.6) 3 (4.2) 4 (7.0) 7 (9.9) 8 (11.3) 71 N95.0 Postmenopausal bleeding 3.7 (2.6–5.2) 0 5 (7.8) 1 (1.6) 0 1 (1.6) 54 (84.4) 3 (4.7) 64 R19.4 Change in bowel habit 3.7 (2.5–5.3) 7 (12.7) 2 (3.6) 4 (7.3) 3 (5.4) 4 (7.3) 1 (1.8) 34 (61.8) 55 1918 Diagnostic codes ICD-10* LR (95% CI) Prostate, n = (%) Breast, n = (%) Skin, n = (%) MMa, n = (%) Lung, n = (%) Gynb, n = (%) CRCc, n = (%) Total, n = (%) N40 Hyperplasia of prostate 2.0 (1.8–2.3) 242 (73.1) 1 (0.3) 26 (7.9) 12 (3.6) 12 (3.6) 0 38 (11.4) 331 R23 Other skin changes 1.8 (1.6–2.1) 40 (13.1) 29 (9.5) 102 (33.3) 85 (27.8) 13 (4.2) 9 (2.9) 28 (9.2) 306 D64 Other anaemias 1.8 (1.5–2.1) 22 (11.2) 18 (9.1) 23 (11.7) 7 (7.2) 10 (5.1) 15 (7.6) 102 (51.8) 197 L57.0 Actinic keratosis 1.8 (1.5–2.1) 30 (18.5) 12 (6.9) 77 (44.5) 20 (11.6) 9 (5.2) 5 (2.9) 20 (11.6) 173 R74 Abnormal serum enzyme levels 4.6 (3.6–5.9) 120 (86.9) 0 2 (1.4) 2 (1.4) 4 (2.9) 0 10 (7.2) 138 D50 Iron deficiency anaemia 2.6 (2.0–3.3) 5 (4.8) 9 (8.6) 7 (6.7) 1 (1.0) 2 (1.9) 6 (5.7) 75 (71.4) 105 N63 Unspecified lump in breast 11.9 (8.0–17.8) 0 97 (96.0) 0 1 (1.0) 0 1 (1.0) 2 (2.0) 101 N42 Other disorder of prostate 2.3 (1.8–3.0) 80 (79.2) 0 2 (2.0) 4 (4.0) 7 (6.7) 0 8 (7.6) 101 D22 Melanocytic naevi 1.8 (1.4–2.3) 25 (25.8) 10 (10.3) 6 (6.2) 41 (42.3) 3 (3.1) 4 (4.1) 8 (8.2) 97 R33 Retention of urine 2.4 (1.8–3.0) 70 (73.7) 1 (1.0) 6 (6.3) 2 (2.1) 2 (2.1) 2 (2.1) 12 (12.6) 95 K62 Other diseases of colon and rectum 2.7 (2.0–3.5) 9 (10.7) 5 (6.0) 6 (7.1) 1 (1.2) 5 (6.0) 3 (3.6) 55 (65.5) 84 R31 Unspecified haematuria 2.2 (1.6–3.0) 40 (56.3) 5 (7.0) 4 (5.6) 3 (4.2) 4 (7.0) 7 (9.9) 8 (11.3) 71 N95.0 Postmenopausal bleeding 3.7 (2.6–5.2) 0 5 (7.8) 1 (1.6) 0 1 (1.6) 54 (84.4) 3 (4.7) 64 R19.4 Change in bowel habit 3.7 (2.5–5.3) 7 (12.7) 2 (3.6) 4 (7.3) 3 (5.4) 4 (7.3) 1 (1.8) 34 (61.8) 55 1918 LR, likelihood ratio calculated between cases and controls. aMalignant melanoma. bGynaecological cancer. cColorectal cancer. *P-value < 0.01. View Large Table 3 Most frequent diagnostic codes related to cancer types Diagnostic codes ICD-10* LR (95% CI) Prostate, n = (%) Breast, n = (%) Skin, n = (%) MMa, n = (%) Lung, n = (%) Gynb, n = (%) CRCc, n = (%) Total, n = (%) N40 Hyperplasia of prostate 2.0 (1.8–2.3) 242 (73.1) 1 (0.3) 26 (7.9) 12 (3.6) 12 (3.6) 0 38 (11.4) 331 R23 Other skin changes 1.8 (1.6–2.1) 40 (13.1) 29 (9.5) 102 (33.3) 85 (27.8) 13 (4.2) 9 (2.9) 28 (9.2) 306 D64 Other anaemias 1.8 (1.5–2.1) 22 (11.2) 18 (9.1) 23 (11.7) 7 (7.2) 10 (5.1) 15 (7.6) 102 (51.8) 197 L57.0 Actinic keratosis 1.8 (1.5–2.1) 30 (18.5) 12 (6.9) 77 (44.5) 20 (11.6) 9 (5.2) 5 (2.9) 20 (11.6) 173 R74 Abnormal serum enzyme levels 4.6 (3.6–5.9) 120 (86.9) 0 2 (1.4) 2 (1.4) 4 (2.9) 0 10 (7.2) 138 D50 Iron deficiency anaemia 2.6 (2.0–3.3) 5 (4.8) 9 (8.6) 7 (6.7) 1 (1.0) 2 (1.9) 6 (5.7) 75 (71.4) 105 N63 Unspecified lump in breast 11.9 (8.0–17.8) 0 97 (96.0) 0 1 (1.0) 0 1 (1.0) 2 (2.0) 101 N42 Other disorder of prostate 2.3 (1.8–3.0) 80 (79.2) 0 2 (2.0) 4 (4.0) 7 (6.7) 0 8 (7.6) 101 D22 Melanocytic naevi 1.8 (1.4–2.3) 25 (25.8) 10 (10.3) 6 (6.2) 41 (42.3) 3 (3.1) 4 (4.1) 8 (8.2) 97 R33 Retention of urine 2.4 (1.8–3.0) 70 (73.7) 1 (1.0) 6 (6.3) 2 (2.1) 2 (2.1) 2 (2.1) 12 (12.6) 95 K62 Other diseases of colon and rectum 2.7 (2.0–3.5) 9 (10.7) 5 (6.0) 6 (7.1) 1 (1.2) 5 (6.0) 3 (3.6) 55 (65.5) 84 R31 Unspecified haematuria 2.2 (1.6–3.0) 40 (56.3) 5 (7.0) 4 (5.6) 3 (4.2) 4 (7.0) 7 (9.9) 8 (11.3) 71 N95.0 Postmenopausal bleeding 3.7 (2.6–5.2) 0 5 (7.8) 1 (1.6) 0 1 (1.6) 54 (84.4) 3 (4.7) 64 R19.4 Change in bowel habit 3.7 (2.5–5.3) 7 (12.7) 2 (3.6) 4 (7.3) 3 (5.4) 4 (7.3) 1 (1.8) 34 (61.8) 55 1918 Diagnostic codes ICD-10* LR (95% CI) Prostate, n = (%) Breast, n = (%) Skin, n = (%) MMa, n = (%) Lung, n = (%) Gynb, n = (%) CRCc, n = (%) Total, n = (%) N40 Hyperplasia of prostate 2.0 (1.8–2.3) 242 (73.1) 1 (0.3) 26 (7.9) 12 (3.6) 12 (3.6) 0 38 (11.4) 331 R23 Other skin changes 1.8 (1.6–2.1) 40 (13.1) 29 (9.5) 102 (33.3) 85 (27.8) 13 (4.2) 9 (2.9) 28 (9.2) 306 D64 Other anaemias 1.8 (1.5–2.1) 22 (11.2) 18 (9.1) 23 (11.7) 7 (7.2) 10 (5.1) 15 (7.6) 102 (51.8) 197 L57.0 Actinic keratosis 1.8 (1.5–2.1) 30 (18.5) 12 (6.9) 77 (44.5) 20 (11.6) 9 (5.2) 5 (2.9) 20 (11.6) 173 R74 Abnormal serum enzyme levels 4.6 (3.6–5.9) 120 (86.9) 0 2 (1.4) 2 (1.4) 4 (2.9) 0 10 (7.2) 138 D50 Iron deficiency anaemia 2.6 (2.0–3.3) 5 (4.8) 9 (8.6) 7 (6.7) 1 (1.0) 2 (1.9) 6 (5.7) 75 (71.4) 105 N63 Unspecified lump in breast 11.9 (8.0–17.8) 0 97 (96.0) 0 1 (1.0) 0 1 (1.0) 2 (2.0) 101 N42 Other disorder of prostate 2.3 (1.8–3.0) 80 (79.2) 0 2 (2.0) 4 (4.0) 7 (6.7) 0 8 (7.6) 101 D22 Melanocytic naevi 1.8 (1.4–2.3) 25 (25.8) 10 (10.3) 6 (6.2) 41 (42.3) 3 (3.1) 4 (4.1) 8 (8.2) 97 R33 Retention of urine 2.4 (1.8–3.0) 70 (73.7) 1 (1.0) 6 (6.3) 2 (2.1) 2 (2.1) 2 (2.1) 12 (12.6) 95 K62 Other diseases of colon and rectum 2.7 (2.0–3.5) 9 (10.7) 5 (6.0) 6 (7.1) 1 (1.2) 5 (6.0) 3 (3.6) 55 (65.5) 84 R31 Unspecified haematuria 2.2 (1.6–3.0) 40 (56.3) 5 (7.0) 4 (5.6) 3 (4.2) 4 (7.0) 7 (9.9) 8 (11.3) 71 N95.0 Postmenopausal bleeding 3.7 (2.6–5.2) 0 5 (7.8) 1 (1.6) 0 1 (1.6) 54 (84.4) 3 (4.7) 64 R19.4 Change in bowel habit 3.7 (2.5–5.3) 7 (12.7) 2 (3.6) 4 (7.3) 3 (5.4) 4 (7.3) 1 (1.8) 34 (61.8) 55 1918 LR, likelihood ratio calculated between cases and controls. aMalignant melanoma. bGynaecological cancer. cColorectal cancer. *P-value < 0.01. View Large Discussion In the study, more than half of all the adult patients with the seven most common cancers had consulted a GP four times or more frequently in the year before cancer diagnosis. The majority of the clinical features associated with cancer had been registered at the fourth or a later consultation. Six out of ten features with the highest LR were alarm symptoms for cancer. However, 17% of the total number of codes had already been registered during the first two GP consultations, and these early clinical features were both alarm symptoms and features with more benign characteristics such as abnormal blood test, change in bowel habit, symptoms from the bladder and prostate and different skin lesions. Another two or more GP consultations were needed before the cancer was diagnosed. To our knowledge, this is the first study to provide information on when the different clinical features were presented at a GP consultation. A major finding of this study was that the majority of cancer patients consulted a GP at least four times before their cancer was diagnosed. This is in contrast with a UK study of national audit data on patients with 18 common and rarer cancers where 18% of the patients with symptoms that were relevant to cancer had three or more consultations (33). Comparing different studies on pre-referral consultations in primary care before cancer diagnosis can be confusing, as some relate to all consultations and others only to those with well-known cancer-related symptoms. A study presenting results concordant with ours reported that when any reason for consultation was considered (as in this study), about three-quarters of colorectal cancer patients had four or more pre-referral consultations in primary care (34). A large UK study from 2012 that was based on a national patient survey reported that 7% of patients with breast cancer and 10% of melanoma patients had three or more pre-referral consultations in primary care before a hospital referral to diagnose cancer (15). The symptoms relevant to the different cancers were defined by the patients. This perspective may, however, result in lost information of earlier unknown features that precede cancer diagnosis. Our study that was based on data collected from reliable databases and did not include any preconceived cancer symptoms showed a different result: 48% of breast cancer patients and 52% of malignant melanoma patients had four or more consultations in primary care before diagnosis (Table 1). Even though we did not have access to electronic medical records with information on when patients consulted for a suspected breast cancer symptom, 94% of all breast cancer patients received the diagnostic code unspecified lump in breast in primary care at the fourth or later consultation (Table 2). This makes us believe that the previous consultations were for other reasons than suspected breast cancer and that once the lump was registered, the patient was swiftly referred to secondary care for diagnosis. A Danish study that compared the patterns of general practice utilization in the period before lung cancer diagnosis reported that more than 72% of the patients had five or more consultations in the 12 months before the diagnosis (35). Face-to-face consultations, home visits and daytime phone calls were defined as consultations. This high proportion of patients with frequent consultations is in line with the findings in our study in which almost 66% of lung cancer patients consulted a GP four or more times in the year before cancer diagnosis. Another Danish study, which studied diagnostic activity in general practice during the year preceding colorectal cancer diagnosis, found that almost 50% of colorectal cancer patients had five or more consultations (36). This is comparable with our study in which more than 65% of patients that were later diagnosed with colorectal cancer consulted a GP four times or more. In our study, lump in breast has a strong association with breast cancer, which also has been shown in a UK study where breast lump was the feature with highest significant risk of breast cancer in symptomatic women in primary care (37). The findings from this study that are of particular interest relate to the early clinical features that were associated with cancer (Table 2). An abnormal serum enzyme level can mean a number of different enzymes such as transaminase but also elevated PSA, which is the main diagnostic pathway today for prostate cancer diagnosis. Change in bowel habit is a clinical feature that especially in younger individuals can be interpreted as a benign symptom. Nevertheless, it is considered being a low-risk-but-not-no-risk symptom of cancer, but especially if combined with rectal bleeding, also belongs to symptoms with an increased risk of colorectal cancer (38–41). Thus, the presence of a significant number of these clinical features during the first two consultations could signal missed diagnostic opportunities and therefore doctors’ delay. As this study is based on codes from a health care database and did not have access to medical records with the reasons for consultations, we do not know whether a patient with more than four consultations before a cancer diagnosis was consulting all four times because of cancer-associated symptoms. Nevertheless, when the patients consulted the GP with early clinical features and had to revisit their GP another two or three times before a diagnosis, one might ask why. Our study depicts in total four main reasons why a patient with a common cancer is not identified after the first or second GP consultation. The first reason is due to a GP not considering certain symptoms and signs quickly enough as potential cancer symptoms, for example, abnormal serum enzymes and/or plasma protein levels and a change in bowel habits (42). The second reason is due to the GP acknowledging a symptom or sign as alarming, but because medical investigation is time consuming, needing at least two more consultations before the final examination that diagnoses cancer. Iron deficiency anaemia, which needs a bowel exam before a colorectal cancer is diagnosed, is such an example. The third reason is that the patients’ symptoms suggested a benign disease of the prostate, digestive system or skin, and the GP used the watchful-waiting tool (43). An interesting observation is that codes for symptoms and diseases of the respiratory system were absent in our study sample even though lung cancer patients were included. This could explain why it is so hard to suspect lung cancer early, with the consequences being late diagnosis (44). The fourth reason is simply due to cancer patients with comorbid conditions consulting for other medical problems than those emanating from cancer in the year before cancer diagnosis. One of the key messages in this study is that an un-neglectable proportion of patients that had presented with early clinical features at the first two GP consultations were not swiftly acted upon by the GPs. Thus, these consultations represented missed diagnostic opportunities and therefore delayed cancer diagnosis, which has also been acknowledged in other studies (21,45). The literature reports that 40%–50% of the patients that consult a GP and are later diagnosed with cancer present with alarm symptoms (46,47). This study confirms the figures on alarm symptoms in patients with frequent consultations but differs in the sense that more than half of the patients that had early clinical features associated with cancer did not present with diffuse symptomatology such as pain or fatigue but with focal features with benign characteristics. A strength of our study is that it is based on a total population. All the adult patients with the seven most common cancers in a large region in Sweden were included. Another strength is the use of reliable regional and national databases with almost complete coverage of cancer diagnoses and diagnostic codes from primary care. As the diagnostic codes were registered before the cancer diagnosis and were automatically retrieved, selection bias has been avoided. As it is mandatory for Swedish GPs to code because of the reimbursement system, an extensive and reliable amount of data are available. All diagnostic codes have been collected, not just those preconceived as being well-known symptoms of cancer. One limitation of the study is that the coded information from the health care databases might not have captured all the symptoms and the clinical features presented by the patients and registered in the electronic medical record (48). This has been observed in other fields of research in primary care databases, such as that of rheumatoid arthritis (44). The time span used in our study may also be a limitation. Even though many studies suggest that most cancer symptoms occur 3–6 months before a cancer diagnosis (18,36,49), a longer time span might be needed. Another limitation is that the data analysis was done in a sample with an uneven number of the different cancers. As patients with prostate, colorectal and breast cancer represented 62% of the seven cancers in this study, the diagnostic codes from these patients have probably resulted in a higher LR, than if all the cancers were equally represented. A weakness of our study is that no respiratory symptoms associated with lung cancer were found, which could depend on either an underregistration of these symptoms by the GPs, or lung cancer patients being too few (10%) in proportion to all the other cancers in our study. Conclusion More than half of the patients with common cancers had consulted a GP at least four times in the year before their cancer diagnosis. One out of six clinical features that they presented already at the two first consultations were focal and had benign characteristics. These features might have been missed diagnostic opportunities. A more vigilant approach towards patients presenting in primary care with these clinical features could result in timelier cancer diagnoses. Acknowledgements The authors thank Erik Holmberg PhD, statistician at Regional Cancer Centre West for the extraction of data from the SCR. We also thank Kristina Narbro PhD and Mona–Lis Dalbrekt, Department of Health Care Evaluation, County Council, Västra Götaland Region, for help in the extraction of data from the regional health care database. Declaration Funding: The study was conducted without external funding. 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Br J Cancer 2015 ; 112 : 271 – 7 . Google Scholar Crossref Search ADS PubMed © The Author(s) 2018. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model)

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Family PracticeOxford University Press

Published: Sep 18, 2018

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