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Time to Treatment Initiation and Survival in Adult Localized High-Grade Bone Sarcoma

Time to Treatment Initiation and Survival in Adult Localized High-Grade Bone Sarcoma Hindawi Sarcoma Volume 2020, Article ID 2984043, 9 pages https://doi.org/10.1155/2020/2984043 Research Article Time to Treatment Initiation and Survival in Adult Localized High-Grade Bone Sarcoma 1 2 3 4 5 Joshua M. Lawrenz , Joseph Featherall, Gannon L. Curtis, Jaiben George, Yuxuan Jin, 5 5 5 5 Peter M. Anderson, Dale R. Shepard, John D. Reith , Brian P. Rubin, 5 5 Lukas M. Nystrom , and Nathan W. Mesko Vanderbilt University Medical Center, Nashville, TN 37232, USA University of Utah Hospital, Salt Lake City, UT 84132, USA University Health Center, Wayne State University, Detroit, MI 48201, USA AIIMS Hospital, New Delhi, India Cleveland Clinic, Cleveland, OH 44195, USA Correspondence should be addressed to Joshua M. Lawrenz; josh.lawrenz@gmail.com Received 16 February 2020; Accepted 15 April 2020; Published 5 May 2020 Academic Editor: Valerae O. Lewis Copyright © 2020 Joshua M. Lawrenz et al. +is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Objective. Few studies have evaluated the prognostic implication of the length of time from diagnosis to treatment initiation in bone sarcoma. +e purpose of this study is to determine if time to treatment initiation (TTI) influences overall survival in adults diagnosed with primary bone sarcoma. Methods. A retrospective analysis of the National Cancer Database identified 2,122 patients who met inclusion criteria with localized, high-grade bone sarcoma diagnosed between 2004 and 2012. TTI was defined as length of time in days from diagnosis to initiation of treatment. Patient, disease-specific, and healthcare-related factors were also assessed for their association with overall survival. Kruskal-Wallis analysis was utilized for univariate analysis, and Cox regression modeling identified covariates associated with overall survival. Results. Any 10-day increase in TTI was not associated with decreased overall survival (hazard ratio (HR) � 1.00; P � 0.72). No differences in survival were detected at 1 year, 5 years, and 10 years, when comparing patients with TTI � 14, 30, 60, 90, and 150 days. Decreased survival was significantly associated (P< 0.05) with patient ages of 51–70 years (HR � 1.66; P � 0.004) and> 71 years (HR � 2.89; P< 0.001), Charlson/Deyo score≥2 (HR � 2.02; P< 0.001), pelvic tumor site (HR � 1.58; P< 0.001), tumor size >8 cm (HR � 1.52; P< 0.001), radiation (HR � 1.81; P< 0.001) as index treatment, and residing a distance of 51–100 miles from the treatment center (HR � 1.30; P � 0.012). Increased survival was significantly associated (P< 0.05) with chordoma (HR � 0.27; P � 0.010), chondrosarcoma (HR � 0.75; P � 0.002), treatment at an academic center (HR � 0.64; P � 0.039), and a private (HR � 0.67; P � 0.006) or Medicare (HR � 0.71; P � 0.043) insurer. A transition in care was not associated with a survival disadvantage (HR � 0.90; P � 0.14). Conclusions. Longer TTI was not associated with decreased overall survival in localized, high-grade primary bone sarcoma in adults. +is is important in counseling patients, who may delay treatment to receive a second opinion or seek referral to a higher volume sarcoma center. argues for earlier diagnosis and treatment [2, 3]. Time to 1. Introduction treatment initiation (TTI), defined as the duration of time Primary bone sarcomas are rare malignancies with a na- between diagnosis and the initiation of treatment, has be- tional incidence in the United States of around 3,200 cases come an important quality metric in cancer care, as the annually and a five-year relative survival between 60 and length of this time period can potentially affect patient 70% in localized disease [1]. Prognosis in bone sarcoma is anxiety and outcome. Registry data for breast and head and closely correlated with tumor grade and disease stage, which neck cancers have demonstrated an association between 2 Sarcoma increased treatment wait times and decreased survival [4, 5]. limited to patients with high grade, localized disease. +e It is arguable that the potential benefits of shorter TTI would inclusion criteria can be found in Figure 1. apply to most, if not all, cancers, including high-grade bone sarcoma. Despite the obvious benefits of expedited treat- 2.2. Outcome Measures. +e primary objective of this study ment, other factors such as treatment at an established was to evaluate the association between TTI and OS in multidisciplinary sarcoma program are believed to positively patients with localized, high-grade bone sarcoma. TTI was affect prognosis but may result in a treatment delay due to defined as the time in days between confirmed tissue di- coordination and transfer of care [6–8]. +us, the inquiry as agnosis and initiation of any definitive treatment course to if TTI affects prognosis in bone sarcoma is nuanced, and (surgical resection, systemic chemotherapy, and radiation the rarity of the disease has led to limited data addressing therapy). Diagnostic or palliative procedures do not qualify this issue [9]. as treatment initiation. OS was defined as the time in months +e National Cancer Database (NCDB) is a high-quality from treatment initiation until death or the patient’s last cancer registry that captures data from newly diagnosed follow-up visit. Patient, healthcare, and tumor characteris- cancers in the United States and is of particular value when tics (Table 1) were also collected to investigate their asso- investigating rare cancers such as bone sarcoma [10]. +e ciations with patient OS. Patient demographics included age, NCDB has been utilized to investigate the correlation be- gender, race, Charlson/Deyo Score (CDS) (0, 1, or >2), and tween time to treatment and survival in other cancer types in annual income. It is important to note that annual income is effort to reduce delays and improve outcomes [4, 5, 11]. In a not patient derived data, but rather the mean income re- recent inquiry of the effect of TTI on survival in soft tissue ported in the patient’s zip code. Tumor factors included sarcoma, TTI was found to have minimal effect on overall histology, primary site, size, grade, clinical stage, and initial survival (OS), with a delay of greater than 42 days having a definitive treatment modality. Healthcare system factors trend toward decreasing survival [7]. No similar studies have included treating facility type, insurance provider, distance been performed with the primary goal to establish this from the patient’s residence to the treating facility, and correlation in bone sarcoma. presence of a transition in care. Patients who received a +e primary aim of this study was to determine if TTI diagnosis at one facility and had initial treatment com- influences OS in patients diagnosed with localized, high- mencement at another facility were considered to have a grade bone sarcoma. We hypothesized that prolonged TTI transition in care. Facility type was divided into community would be associated with decreased survival in bone sar- cancer programs, comprehensive cancer centers, academic coma patients. Additionally, the secondary aim was to centers, integrated network cancer programs, and other. identify patient socioeconomic, tumor-specific, and Community cancer programs are defined as having 100–500 healthcare-related factors that contribute to bone sarcoma new cancer cases a year, whereas comprehensive cancer survival. programs are defined as diagnosing>500 new cancer cases a year. “New cancer cases” are defined as all histologic di- 2. Methods agnoses, not exclusively sarcoma. Community programs offer both diagnostic and treatment services, although what 2.1. Database and Selection of Patients. Following approval specific treatment services offered for rare malignancies such by our institutional review board, the NCDB was reviewed as sarcoma are unknown. Integrated network cancer pro- from 2004 to 2012. Created in 1989 by the American College grams usually have a “unified cancer committee” and consist of Surgeons (ACS) and the Commission on Cancer (CoC), of “multiple facilities providing comprehensive services” the NCDB captures 70% of all new United States cancer [15]. Academic institutions are defined with the same patient diagnoses and collects data from over 1,500 cancer centers volume definition as a comprehensive cancer center but also [12]. +e methodology for reporting to the NCDB has been have a noted resident/medical education program. previously described [8]. Adult patients (≥18 years old) with bone sarcoma diagnosed between 2004 and 2012 were identified using topographical codes (C40.0-C40.3, C40.8- 2.3. Statistical Analysis. +e number of patients and fre- C41.4, C41.8, C41.9) designated by International Classifi- quencies for all independent categorical variables were re- ported. Median TTI was reported given the nonparametric cation of Disease for Oncology, +ird Edition [ICD-O-3]. A patient also required an ICD-O-3 histology code consistent dataset and was compared across different levels of the same categorical variable by using Kruskal-Wallis tests. +e re- with a bone sarcoma to be included. +ese codes identified a total of 13,329 patients with a bone sarcoma. Patients were lationship between OS and TTI, along with other important excluded for the following reasons: (1) lack of follow-up or secondary covariates such as age, gender, race, and treatment essential data (n � 1,485), (2) American Joint Committee on modality were examined with Cox regression modeling. Cancer (AJCC) Stage IV or unknown stage disease Hazard ratios (HR) and 95% confidence intervals (CI) were (n � 5,686), and (3) well differentiated (grade 1), moderately determined for each variable. +e TTI variable was entered differentiated (grade 2), or unknown grade (n � 4,036). +us, into the full Cox regression by using four-knot restricted cubic splines to allow for a nonlinear relationship between 2,122 adult patients with localized, high-grade disease were included in the final analysis. Given the significant impact TTI and the survival outcome [16]. However, the spline effect was not significant. Given the nonsignificant and tumor grade and disease stage have been shown to have on survival outcome [9, 13, 14], this cohort was intentionally nonlinear relationship of TTI with survival in all TTI Sarcoma 3 Table 1: Continued. 13,329 patients identified Factor Total (N � 2,122) Transition in care 1,485 with missing data No 1,137 (53.6%) Excluded 5,686 with stage IV or Yes 985 (46.4%) unknown disease Year of diagnosis 2004 160 (7.5%) 4,036 with grades 1, 2 or unknow grade 2005 213 (10.0%) 2006 226 (10.7%) 2,122 patients included in 2007 202 (9.5%) analysis 2008 244 (11.5%) 2009 273 (12.9%) Figure 1: Study cohort inclusion criteria. 2010 274 (12.9%) 2011 267 (12.6%) 2012 263 (12.4%) Primary tumor site Table 1: Demographic data. Upper extremity 281 (13.2%) Lower extremity 985 (46.4%) Factor Total (N � 2,122) Pelvis 344 (16.2%) Time to treatment initiation, days (IQR) 25.0 [12.0, 42.0] Other 512 (24.1%) Age Tumor size 18–30 654 (30.8%) ≤8.0 cm 967 (45.6%) 31–50 555 (26.2%) >8.0 cm 1,155 (54.4%) 51–70 627 (29.5%) Grade 71+ 286 (13.5%) Poorly differentiated 1,253 (59.0%) Sex Undifferentiated 869 (41.0%) Male 1,241 (58.5%) Clinical staging Female 881 (41.5%) Stage I 239 (11.3%) Race Stage II 1,782 (84.0%) White 1,735 (81.8%) Stage III 101 (4.8%) Black 258 (12.2%) First-line treatment modality Other/unknown 129 (6.1%) Surgery 1,029 (48.5%) Charlson/Deyo score Radiation 86 (4.1%) 0 1,843 (86.9%) Systemic 994 (46.8%) 1 222 (10.5%) Multimodal 13 (0.61%) ≥2 57 (2.7%) Vital status Histology Died 922 (43.4%) Osteosarcoma 1,217 (57.4%) Alive 1,200 (56.6%) Chondrosarcoma 486 (22.9%) Statistics presented as median [P25, P75] or N (column %). Community Ewing’s sarcoma 195 (9.2%) cancer program: between 100 and 500 new cancer cases annually, Com- Chordoma 17 (0.80%) prehensive community cancer program: >500 new cancer cases annually, Other 207 (9.8%) academic center: >500 new cancer cases annually and resident/medical Facility type education, integrated network: multiple facilities providing comprehensive Comm. cancer prg. 38 (1.8%) services with a unified cancer committee. comm., community; prg., Comprehensive comm. cancer prg. 286 (13.5%) program. Academic center 856 (40.3%) Integrated network cancer prg. 62 (2.9%) Other/unknown 880 (41.5%) cohorts, cubic spline modeling of HR according to TTI as a Insurance continuous variable was not performed. After specifying Uninsured 120 (5.7%) different TTI values (TTI � 14, 30, 60, 90, and 150 days) and Private insurance 1,148 (54.1%) by setting the covariates to their reference levels, the 1-year, Medicaid 258 (12.2%) 5-year, and 10-year survival probabilities were determined Medicare 454 (21.4%) and associated survival curves were plotted. Statistical an- Other/unknown 142 (6.7%) alyses were completed with SAS software (Version 9.4; Cary, Income NC). +e multivariable cox regression model was built using <$38,000 404 (19.0%) rms package in R software (Version 3.4; Vienna, Austria). $38,000-$47,999 500 (23.6%) $48,000-$62,999 563 (26.5%) All tests were two-sided, with an alpha level of 0.05. P values $63,000+ 655 (30.9%) less than 0.05 were considered significant. Distance from facility <21 miles 974 (45.9%) 3. Results 21–50 miles 466 (22.0%) 51–100 miles 306 (14.4%) 3.1. TTI and Survival. Overall survival probabilities dem- >100 miles 376 (17.7%) onstrated minimal differences at 1 year, 5 years, and 10 years 4 Sarcoma Table 2: 1-year, 5-year, and 10-year survival probabilities based at TTI � 14, 30, 60, 90, and 150 days (Table 2). Similarly, upon time to treatment initiation. adjusted survival curves generated by Cox regression modeling were near identical out to 10 years (HR � 1.00; Time Survival probability 95% CI P � 0.72) (Figure 2). TTI � 14 1 year 0.84 0.74 0.95 5 years 0.46 0.26 0.79 3.2. Factors 3at Influence Survival. Univariate analysis 10 years 0.36 0.18 0.74 revealed significant differences seen in regard to the rela- TTI � 30 tionship of TTI with several secondary variables (Table 3). 1 year 0.84 0.74 0.95 Multivariable analysis also identified several secondary pa- 5 years 0.46 0.26 0.79 tient, tumor, treatment, and healthcare system related fac- 10 years 0.36 0.18 0.74 TTI � 60 tors associated with mortality (Table 4). +ose that were 1 year 0.84 0.74 0.95 statistically significant are highlighted in Figure 3. Patient 5 years 0.46 0.27 0.80 factors such as age between 51 and 70 (HR = 1.66; P � 0.004) 10 years 0.37 0.18 0.75 and age of 71+ (HR = 2.89; P< 0.001) and patients with a TTI � 90 Charlson/Deyo score ≥2 (HR = 2.02; P< 0.001) were asso- 1 year 0.84 0.75 0.95 ciated with decreased survival, whereas sex, race, and income 5 years 0.46 0.27 0.80 were not associated with survival. A diagnosis of chon- 10 years 0.37 0.18 0.75 drosarcoma (HR = 0.75; P � 0.002), chordoma (HR = 0.27; TTI � 150 P � 0.01), or other bone sarcoma not including Ewing’s 1 year 0.85 0.75 0.96 sarcoma (HR = 0.75; P � 0.022) all were associated with 5 years 0.47 0.27 0.82 increased survival when compared to osteosarcoma, whereas 10 years 0.38 0.18 0.78 tumors located in the pelvis (HR = 1.58; P< 0.001) and TTI: time to treatment initiation; CI: confidence interval. tumors greater than 8 cm in size (HR = 1.52; P< 0.001) were associated with decreased survival. Being a distance between 1.0 51 and 100 miles from the treatment center (HR = 1.30; P � 0.012) compared to being less than 21 miles away was associated with decreased survival, though being greater 0.8 than 100 miles away had no effect. Any year of diagnosis between 2005 and 2012 compared to 2004 did not influence 0.6 prognosis. Patients treated at an academic center (HR = 0.64; P � 0.039) or other noncategorized center (HR = 0.50; 0.4 P � 0.006) compared to a community cancer program had an association with increased survival. Patients with private insurance (HR = 0.65; P � 0.004) or Medicare insurance 0.2 (HR = 0.71; P � 0.043) had an association with increased survival. Having a transition in care after diagnosis to an- 0.0 other center for treatment did not influence survival out- 0 12 24 36 48 60 72 84 96 108 120 132 come (HR = 0.90; P � 0.14). First-line treatment of radiation Months therapy (HR = 1.81; P< 0.001) when compared to surgery as first treatment had an association with decreased survival. 14 90 Tumor grade and clinical stage did not demonstrate asso- 30 150 ciation with survival, as to be expected in a cohort of only high grade, localized bone sarcomas. Figure 2: Survival curves using different values for time to treatment initiation. +is graph demonstrates the near-identical Kaplan–Meier survival curves when comparing patients with a time 4. Discussion to treatment initiation of 14, 30, 60, 90, and 150 days (HR � 1.00; P � 0.72). +ese data demonstrate that all cause survival probability at one, five, and ten years after diagnosis was no different when comparing patients with a TTI ranging from 0 to 150 days outcome in their cohort of extremity osteosarcomas. In both breast and head and neck cancers, recent registry data have (five months). Factors found to correlate with survival in- cluded patient age, comorbidity index, histologic subtype, shown a correlation between increased treatment wait times primary tumor location and size, initial treatment type, type and decreased survival [4, 5]. Nevertheless, given the of insurance, treating facility type, and distance of home findings of the present study and previous work in soft tissue residence from the treating facility. sarcoma [7], it remains unclear as to why TTI has little Prior data associating treatment delay with survival prognostic implication in sarcoma. outcome in sarcoma is limited, with only a single study that Far more studied is the association between time to compared a treatment delay of less than or greater than three diagnosis and survival, as delay in diagnosis is the most weeks [9]. +e authors concluded no difference on survival common reason for litigation related to the treatment of Survival probability Sarcoma 5 Table 3: Univariate relationships between factors and time to treatment initiation. Factor N TTI, days median [p25, p75] P value Age 0.006 18–30 654 21.0 [13.0, 366.0] 31–50 555 28.0 [14.0, 44.0] 51–70 627 26.0 [12.0, 45.0] 71+ 286 25.5 [7.0, 44.0] Sex 0.52 Male 1241 24.0 [12.0, 42.0] Female 881 26.0 [13.0, 43.0] Race 0.050 White 1735 25.0 [12.0, 42.0] Black 258 28.0 [22.0, 48.0] Other/unknown 129 20.0 [7.0, 44.0] Charlson/Deyo score 0.18 0 1843 25.0 [13.0, 42.0] 1 258 22.0 [9.0, 40.0] ≥2 57 29.0[7.0, 44.0] Histology 0.003 Osteosarcoma 1217 25.0 [13.0, 40.0] Chondrosarcoma 486 27.0 [10.0, 48.0] Ewing’s sarcoma 195 21.0 [11.0, 34.0] Chordoma 17 38.0 [17.0, 77.0] Other 207 29.0 [15.0, 49.0] Facility type <0.001 Comm. cancer prg. 38 32.5 [1.00, 48.0] Comprehensive comm. cancer Prg. 286 21.5 [5.0, 40.0] Academic center 856 27.0 [14.0, 47.0] Integrated network cancer program 62 29.5 [11.0, 52.0] Other/unknown 880 23.0 [13.0, 37.0] Insurance <0.001 Uninsured 120 27.5 [15.0, 43.5] Private insurance 1148 23.0 [12.0, 39.0] Medicaid 258 26.0 [13.0, 43.0] Medicare 454 27.5 [10.0, 48.0] Other/unknown 142 35.0 [19.0, 52.0] Income 0.73 <$38,000 404 25.5 [12.0, 45.5] $38,000–$47,999 500 24.0 [12.0, 40.5] $48,000–$62,999 563 24.0 [11.0, 43.0] $63,000+ 655 26.0 [14.0, 42.0] Distance from facility 0.069 >21 miles 974 25.0 [12.0, 42.0] 21–50 miles 466 24.0 [13.0, 42.0] 51–100 miles 306 23.0 [9.0, 40.0] >100 miles 376 28.0 [14.5, 44.0] Transition in care <0.001 No 1137 20.0 [8.0, 35.0] Yes 985 31.0 [19.0, 49.0] Year of diagnosis 0.25 2004 160 25.5 [9.0, 42.0] 2005 213 27.0 [14.0, 51.0] 2006 226 24.0 [11.0, 39.0] 2007 202 25.5 [13.0, 43.0] 2008 244 25.0 [13.0, 42.0] 2009 273 23.0 [11.0, 39.0] 2010 274 25.5 [14.0, 41.0] 2011 267 27.0 [14.0, 44.0] 2012 263 25.0 [12.0, 42.0] Primary tumor site <0.001 Upper extremity 281 25.0 [14.0, 42.0] Lower extremity 985 22.0 [12.0, 36.0] 6 Sarcoma Table 3: Continued. Factor N TTI, days median [p25, p75] P value Pelvis 344 29.0 [15.0, 49.0] Other 512 28.0 [9.5, 48.0] Tumor size 0.48 ≤8.0 cm 967 26.0 [12.0, 42.0] >8.0 cm 1155 25.0 [13.0, 42.0] Grade 0.63 Poorly differentiated 1253 25.0 [11.0, 43.0] Undifferentiated 869 26.0 [14.0, 42.0] Clinical staging 0.10 Stage I 239 28.0 [14.0, 49.0] Stage II 1782 24.0 [12.0, 42.0] Stage III 101 27.0 [11.0, 45.0] First-line treatment modality <0.001 Surgery 1029 24.0 [6.0, 47.0] Radiation 86 34.5 [19.0, 56.0] Systemic 994 25.0 [15.0, 37.0] Multimodel 13 39.0 [26.0, 47.0] P values correspond to the Kruskal–Wallis test. Comm.: community; prg.: program; TTI: time to treatment initiation. extremity sarcoma [17]. +e traditional legal argument is therapy first, as we suspect this cohort was likely biased toward unresectable tumors or patients undergoing pallia- that the increased time allows for a cancer to grow and spread, leading to worse prognosis. Prior studies have tion. Furthermore, patients who lived a distance of 51–100 evaluated the length of time prior to diagnosis (or duration miles from the treatment center compared to those who of symptoms) in bone sarcoma and have demonstrated no lived <21 miles away had an increased risk of death, despite significant correlation with survival [13, 14]. +is infor- having a shorter median TTI (23 days vs. 25 days, respec- mation is useful when counseling patients who exhibit re- tively). To no surprise, insured status (private insurer or morse or anxiety for not presenting to a physician sooner. Medicare insurer) when compared to being uninsured was Considering the lack of correlation between longer duration found to be associated with increased survival, similar to of symptoms and worsened survival, it is perhaps not recently reported trends seen in prostate, lung, and colo- surprising that TTI (which is typically a much shorter time rectal cancer [18]. Furthermore, our data supported the period than time to diagnosis, 3 weeks [8] vs. 16 weeks [13]), previously noted correlation between receiving care at a high-volume facility and improved survival outcome similarly found no difference. Factors rooted in tumor bi- ology, outside the control of the treating team, are likely a [7, 19, 20]. As well, a transition in care, which previously has powerful confounding factor in understanding the natural been shown to have the greatest correlation with longer TTI history of primary bone sarcoma. [8], was not associated with a survival disadvantage. +is In a 2019 analysis utilizing the NCDB population, supports the concept of referral to a sarcoma referral center Lawrenz et al. identified patient and disease-specific factors with a multidisciplinary treatment team, despite the likely that correlated with TTI in over 13,000 patients with bone delay in treatment initiation. sarcoma, highlighting transitions in care from one treating +is study has several limitations. A retrospective facility to another as being responsible for the greatest in- analysis utilizing multivariable regression only allows for determination of correlation between factors and an out- creases in TTI [8]. Other factors associated with longer TTI included uninsured or government insurer status, nonwhite come, not causation. We recognize there are factors not included in our analysis which remain unaccounted for or race, pelvic tumor location, and treatment at an academic center. A secondary aim of this study was to identify patient, uncontrolled. To this end, we sought to reduce the potential tumor, and healthcare system factors associated with sur- confounding effect of severity of disease and its known vival. Understanding the overwhelming influence tumor strong correlation with prognosis by restricting this cohort grade and disease stage have been shown to have on to only patients with localized, high-grade disease. Despite prognosis [9, 13, 14], this cohort was intentionally limited to this, we recognize this cohort of bone sarcomas consists of patients with high grade, localized disease. Similar to prior multiple histology types, in which there can be differences work, this data reiterates that increased patient age (>51 amongst individual types on prognosis, which may blunt the years), increased tumor size (>8 cm), and pelvic tumor lo- effect of treatment delay in the cohort as a whole. Fur- thermore, national registries are prone to incomplete data cation are correlated with decreased survival, and a diagnosis of chondrosarcoma or chordoma are correlated with in- reporting and even unknown data collection errors. In this dataset, there were 1,485 patients missing time to treatment creased survival [13]. It was not surprising to learn that patients who underwent radiation therapy as first treatment data which we excluded. As well, 40% of patients were (86 patients, 4.1%) had an associated worse prognosis categorized as “other/unknown treatment facility type.” compared to patients who underwent surgery or systemic Given that this was not a critical factor in assessing our Sarcoma 7 Table 4: Multivariate analysis of factors associated with survival. 95% Hazard Factors hazard P values ratio ratio CI TTI—a 10-day increase from day 14 1.00 0.98 1.02 0.72 TTI—a 10-day increase from day 30 1.00 0.98 1.02 0.72 Time to treatments, days TTI—a 10-day increase from day 60 1.00 0.98 1.02 0.72 TTI—a 10-day increase from day 90 1.00 0.98 1.02 0.72 TTI—a 10-day increase from day 150 1.00 0.98 1.02 0.72 31–50 vs. 18–30 1.16 0.88 1.51 0.29 Age group, years 51–70 vs. 18–30 1.66 1.17 2.34 0.004 71+ vs. 18–30 2.89 1.95 4.28 <0.001 Sex Female vs. male 0.94 0.82 1.07 0.33 Black vs. white 0.94 0.75 1.17 0.59 Race Other/unknown vs. white 0.98 0.73 1.31 0.88 1 vs. 0 1.11 0.90 1.36 0.34 Charlson/Deyo score ≥2 vs. 0 2.02 1.45 2.81 <0.001 $38,000–$47,999 vs. <$38,000 1.08 0.88 1.33 0.45 Income $48,000–$62,999 vs. <$38,000 1.03 0.84 1.27 0.75 $63,000+ vs. <$38,000 1.04 0.84 1.29 0.70 Private insurance vs. uninsured 0.65 0.49 0.87 0.004 Medicaid vs. uninsured 0.85 0.61 1.18 0.33 Insurance Medicare vs. uninsured 0.71 0.51 0.99 0.043 Other/unknown vs. uninsured 0.75 0.51 1.10 0.15 Comprehensive community cancer program vs. community cancer 0.89 0.58 1.39 0.62 program Facility type Academic center vs. community cancer program 0.64 0.41 0.98 0.039 Integrated network cancer program vs. community cancer program 0.99 0.58 1.68 0.97 Other/unknown vs. community cancer program 0.50 0.30 0.82 0.006 21–50 miles vs. <21 miles 1.17 0.98 1.39 0.088 Distance from facility 51–100 miles vs. <21 miles 1.30 1.06 1.59 0.012 >100 miles vs. <21 miles 1.08 0.88 1.33 0.44 Transition in care Yes vs. No 0.90 0.78 1.04 0.14 2005 vs. 2004 1.06 0.79 1.41 0.71 2006 vs. 2004 0.84 0.63 1.13 0.26 2007 vs. 2004 1.18 0.88 1.58 0.27 2008 vs. 2004 0.84 0.62 1.13 0.25 Year of diagnosis 2009 vs. 2004 0.90 0.67 1.21 0.48 2010 vs. 2004 1.00 0.74 1.35 0.99 2011 vs. 2004 1.22 0.90 1.65 0.19 2012 vs. 2004 1.06 0.76 1.47 0.73 Radiation vs. surgery 1.81 1.35 2.42 <0.001 First-line treatment Systemic vs. surgery 1.17 0.99 1.39 0.06 modality Multimodal vs. surgery 0.60 0.24 1.49 0.27 Chondrosarcoma vs. osteosarcoma 0.75 0.62 0.90 0.002 Ewing’s sarcoma vs. osteosarcoma 0.82 0.62 1.09 0.17 Histology Chordoma vs. osteosarcoma 0.27 0.10 0.73 0.01 Other vs. osteosarcoma 0.75 0.59 0.96 0.022 Lower extremity vs. upper extremity 0.92 0.75 1.13 0.42 Primary tumor site Pelvis vs. upper extremity 1.58 1.26 1.99 <0.001 Other vs. upper extremity 1.05 0.83 1.32 0.70 Tumor size >8.0 cm vs. ≤8.0 cm 1.52 1.32 1.76 <0.001 Grade Undifferentiated vs. poorly differentiated 1.07 0.94 1.23 0.31 Stage II vs. stage I 0.96 0.77 1.20 0.72 Clinical staging Stage III vs. stage I 0.97 0.69 1.38 0.87 TTI: time to treatment initiation; CI: confidence interval. primary endpoint, we included these patients for the sake of when studying a rare disease such as sarcoma, tools such as increased sample size, though making conclusions regarding the NCDB though imperfect provide a large cohort to in- this specific variable more difficult to interpret. Despite this, vestigate important questions for the purposes of data 8 Sarcoma Age > 71 2.89 Charloson/Deyo score ≥ 2 2.02 Radiation therapy 1.81 Age 51–70 1.66 Pelvic tumor site 1.58 Tumor size > 8 cm 1.52 Distance 51–100 miles 1.3 Chondrosarcoma 0.75 Other PBS diagnosis 0.75 Medicare insurance 0.71 Private insurance 0.65 Academic center 0.64 Other/unknown center 0.5 Chordoma 0.27 Hazard ratio Figure 3: Comparison of relative association between covariates and survival. Only covariates with statistically significant higher (red) or lower (green) HR are shown. description and hypothesis generation. +ese limitations rather than the length of time from when a diagnosis is made could be largely improved upon with a multi-institutional and when treatment is initiated. +is is important in coun- prospective registry effort focused on sarcoma diagnoses. seling patients, who may delay treatment to receive a second In conclusion, this analysis of the NCDB from 2004 to opinion or seek referral to a higher volume sarcoma center. 2012 demonstrates TTI does not correlate with overall sur- vival in localized, high-grade primary bone sarcoma in adults. Data Availability +e primary and secondary conclusions of this data suggest that factors inherent to the patient, disease process, and +e data used to support the findings of this study are in- treating facility are likely more integral to overall prognosis, cluded within the article. Covariate Sarcoma 9 [16] A. Jemal, R. C. Tiwari, T. Murray et al., “Cancer statistics, Conflicts of Interest 2004,” CA: A Cancer Journal for Clinicians, vol. 54, no. 1, pp. 8–29, 2004. +e authors declare that there are no conflicts of interest [17] N. W. Mesko, J. L. Mesko, L. M. Gaffney, J. L. Halpern, related to this work. H. S. Schwartz, and G. E. Holt, “Medical malpractice and sarcoma care-a thirty-three year review of case resolutions, References inciting factors, and at risk physician specialties surrounding a rare diagnosis,” Journal of Surgical Oncology, vol. 110, no. 8, [1] N. Howlader, A. Noone, and M. Krapcho, SEER Cancer pp. 919–929, 2014. Statistics Review, National Cancer Institute, Bethesda, MD, [18] L. Ellis, A. J. Canchola, D. Spiegel, U. Ladabaum, R. Haile, and USA, 2017. S. L. Gomez, “Trends in cancer survival by health insurance [2] R. J. Grimer, “Size matters for sarcomas!” 3e Annals of 3e status in California from 1997 to 2014,” JAMA Oncology, Royal College of Surgeons of England, vol. 88, no. 6, vol. 4, no. 3, pp. 317–323, 2018. pp. 519–524, 2006. [19] J. C. Gutierrez, E. A. Perez, F. L. Moffat, A. S. Livingstone, [3] R. J. Grimer and T. W. R. Briggs, “Earlier diagnosis of bone D. Franceschi, and L. G. Koniaris, “Should soft tissue sar- and soft-tissue tumours,” 3e Journal of Bone and Joint comas be treated at high-volume centers?” Annals of Surgery, Surgery. British Volume, vol. 92, no. 11, pp. 1489–1492, 2010. vol. 245, no. 6, pp. 952–958, 2007. [4] R. J. Bleicher, K. Ruth, E. R. Sigurdson et al., “Time to surgery [20] A. L. Lazarides, D. L. Kerr, D. P. Nussbaum et al., “Soft tissue and breast cancer survival in the United States,” JAMA On- sarcoma of the extremities,” Clinical Orthopaedics and Related cology, vol. 2, no. 3, pp. 330–339, 2016. Research, vol. 477, no. 4, pp. 718–727, 2019. [5] C. T. Murphy, T. J. Galloway, E. A. Handorf et al., “Survival impact of increasing time to treatment initiation for patients with head and neck cancer in the United States,” Journal of Clinical Oncology, vol. 34, no. 2, pp. 169–178, 2016. [6] O. Zaikova, K. Sundby Hall, E. Styring et al., “Referral pat- terns, treatment and outcome of high-grade malignant bone sarcoma in Scandinavia-SSG Central Register 25 years’ ex- perience,” Journal of Surgical Oncology, vol. 112, no. 8, pp. 853–860, 2015. [7] J. Featherall, G. L. Curtis, J. M. Lawrenz et al., “Time to treatment initiation and survival in adult localized, high-grade soft tissue sarcoma,” Journal of Surgical Oncology, vol. 120, no. 7, pp. 1241–1251, 2019. [8] J. M. Lawrenz, G. L. Curtis, J. F. Styron et al., “Adult primary bone sarcoma and time to treatment initiation: an analysis of the National Cancer Database,” Sarcoma, vol. 2018, Article ID 1728302, 9 pages, 2018. [9] S. S. Bielack, B. Kempf-Bielack, G. Delling et al., “Prognostic factors in high-grade osteosarcoma of the extremities or trunk: an analysis of 1,702 patients treated on neoadjuvant cooperative osteosarcoma study group protocols,” Journal of Clinical Oncology, vol. 20, no. 3, pp. 776–790, 2002. [10] T. A. Damron, W. G. Ward, and A. Stewart, “Osteosarcoma, chondrosarcoma, and Ewing’s sarcoma,” Clinical Orthopae- dics and Related Research, vol. 459, pp. 40–47, 2007. [11] C. T. Murphy, T. J. Galloway, E. A. Handorf et al., “Increasing time to treatment initiation for head and neck cancer: an analysis of the National Cancer Database,” Cancer, vol. 121, no. 8, pp. 1204–1213, 2015. [12] S. Mohanty and K. Y. Bilimoria, “Comparing national cancer registries: the National Cancer Data Base (NCDB) and the surveillance, epidemiology, and end results (SEER) program,” Journal of Surgical Oncology, vol. 109, no. 7, pp. 629-630, 2014. [13] J. M. Lawrenz, J. F. Styron, M. Parry, R. J. Grimer, and N. W. Mesko, “Longer duration of symptoms at the time of presentation is not associated with worse survival in primary bone sarcoma,” 3e Bone & Joint Journal, vol. 100, no. 5, pp. 652–661, 2018. [14] B. T. Rougraff, K. Davis, and J. Lawrence, “Does length of symptoms before diagnosis of sarcoma affect patient sur- vival?” Clinical Orthopaedics and Related Research, vol. 462, pp. 181–189, 2007. [15] National Cancer Data Base—Data Dictionary PUF, 2014. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Sarcoma Hindawi Publishing Corporation

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Copyright © 2020 Joshua M. Lawrenz et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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Abstract

Hindawi Sarcoma Volume 2020, Article ID 2984043, 9 pages https://doi.org/10.1155/2020/2984043 Research Article Time to Treatment Initiation and Survival in Adult Localized High-Grade Bone Sarcoma 1 2 3 4 5 Joshua M. Lawrenz , Joseph Featherall, Gannon L. Curtis, Jaiben George, Yuxuan Jin, 5 5 5 5 Peter M. Anderson, Dale R. Shepard, John D. Reith , Brian P. Rubin, 5 5 Lukas M. Nystrom , and Nathan W. Mesko Vanderbilt University Medical Center, Nashville, TN 37232, USA University of Utah Hospital, Salt Lake City, UT 84132, USA University Health Center, Wayne State University, Detroit, MI 48201, USA AIIMS Hospital, New Delhi, India Cleveland Clinic, Cleveland, OH 44195, USA Correspondence should be addressed to Joshua M. Lawrenz; josh.lawrenz@gmail.com Received 16 February 2020; Accepted 15 April 2020; Published 5 May 2020 Academic Editor: Valerae O. Lewis Copyright © 2020 Joshua M. Lawrenz et al. +is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Objective. Few studies have evaluated the prognostic implication of the length of time from diagnosis to treatment initiation in bone sarcoma. +e purpose of this study is to determine if time to treatment initiation (TTI) influences overall survival in adults diagnosed with primary bone sarcoma. Methods. A retrospective analysis of the National Cancer Database identified 2,122 patients who met inclusion criteria with localized, high-grade bone sarcoma diagnosed between 2004 and 2012. TTI was defined as length of time in days from diagnosis to initiation of treatment. Patient, disease-specific, and healthcare-related factors were also assessed for their association with overall survival. Kruskal-Wallis analysis was utilized for univariate analysis, and Cox regression modeling identified covariates associated with overall survival. Results. Any 10-day increase in TTI was not associated with decreased overall survival (hazard ratio (HR) � 1.00; P � 0.72). No differences in survival were detected at 1 year, 5 years, and 10 years, when comparing patients with TTI � 14, 30, 60, 90, and 150 days. Decreased survival was significantly associated (P< 0.05) with patient ages of 51–70 years (HR � 1.66; P � 0.004) and> 71 years (HR � 2.89; P< 0.001), Charlson/Deyo score≥2 (HR � 2.02; P< 0.001), pelvic tumor site (HR � 1.58; P< 0.001), tumor size >8 cm (HR � 1.52; P< 0.001), radiation (HR � 1.81; P< 0.001) as index treatment, and residing a distance of 51–100 miles from the treatment center (HR � 1.30; P � 0.012). Increased survival was significantly associated (P< 0.05) with chordoma (HR � 0.27; P � 0.010), chondrosarcoma (HR � 0.75; P � 0.002), treatment at an academic center (HR � 0.64; P � 0.039), and a private (HR � 0.67; P � 0.006) or Medicare (HR � 0.71; P � 0.043) insurer. A transition in care was not associated with a survival disadvantage (HR � 0.90; P � 0.14). Conclusions. Longer TTI was not associated with decreased overall survival in localized, high-grade primary bone sarcoma in adults. +is is important in counseling patients, who may delay treatment to receive a second opinion or seek referral to a higher volume sarcoma center. argues for earlier diagnosis and treatment [2, 3]. Time to 1. Introduction treatment initiation (TTI), defined as the duration of time Primary bone sarcomas are rare malignancies with a na- between diagnosis and the initiation of treatment, has be- tional incidence in the United States of around 3,200 cases come an important quality metric in cancer care, as the annually and a five-year relative survival between 60 and length of this time period can potentially affect patient 70% in localized disease [1]. Prognosis in bone sarcoma is anxiety and outcome. Registry data for breast and head and closely correlated with tumor grade and disease stage, which neck cancers have demonstrated an association between 2 Sarcoma increased treatment wait times and decreased survival [4, 5]. limited to patients with high grade, localized disease. +e It is arguable that the potential benefits of shorter TTI would inclusion criteria can be found in Figure 1. apply to most, if not all, cancers, including high-grade bone sarcoma. Despite the obvious benefits of expedited treat- 2.2. Outcome Measures. +e primary objective of this study ment, other factors such as treatment at an established was to evaluate the association between TTI and OS in multidisciplinary sarcoma program are believed to positively patients with localized, high-grade bone sarcoma. TTI was affect prognosis but may result in a treatment delay due to defined as the time in days between confirmed tissue di- coordination and transfer of care [6–8]. +us, the inquiry as agnosis and initiation of any definitive treatment course to if TTI affects prognosis in bone sarcoma is nuanced, and (surgical resection, systemic chemotherapy, and radiation the rarity of the disease has led to limited data addressing therapy). Diagnostic or palliative procedures do not qualify this issue [9]. as treatment initiation. OS was defined as the time in months +e National Cancer Database (NCDB) is a high-quality from treatment initiation until death or the patient’s last cancer registry that captures data from newly diagnosed follow-up visit. Patient, healthcare, and tumor characteris- cancers in the United States and is of particular value when tics (Table 1) were also collected to investigate their asso- investigating rare cancers such as bone sarcoma [10]. +e ciations with patient OS. Patient demographics included age, NCDB has been utilized to investigate the correlation be- gender, race, Charlson/Deyo Score (CDS) (0, 1, or >2), and tween time to treatment and survival in other cancer types in annual income. It is important to note that annual income is effort to reduce delays and improve outcomes [4, 5, 11]. In a not patient derived data, but rather the mean income re- recent inquiry of the effect of TTI on survival in soft tissue ported in the patient’s zip code. Tumor factors included sarcoma, TTI was found to have minimal effect on overall histology, primary site, size, grade, clinical stage, and initial survival (OS), with a delay of greater than 42 days having a definitive treatment modality. Healthcare system factors trend toward decreasing survival [7]. No similar studies have included treating facility type, insurance provider, distance been performed with the primary goal to establish this from the patient’s residence to the treating facility, and correlation in bone sarcoma. presence of a transition in care. Patients who received a +e primary aim of this study was to determine if TTI diagnosis at one facility and had initial treatment com- influences OS in patients diagnosed with localized, high- mencement at another facility were considered to have a grade bone sarcoma. We hypothesized that prolonged TTI transition in care. Facility type was divided into community would be associated with decreased survival in bone sar- cancer programs, comprehensive cancer centers, academic coma patients. Additionally, the secondary aim was to centers, integrated network cancer programs, and other. identify patient socioeconomic, tumor-specific, and Community cancer programs are defined as having 100–500 healthcare-related factors that contribute to bone sarcoma new cancer cases a year, whereas comprehensive cancer survival. programs are defined as diagnosing>500 new cancer cases a year. “New cancer cases” are defined as all histologic di- 2. Methods agnoses, not exclusively sarcoma. Community programs offer both diagnostic and treatment services, although what 2.1. Database and Selection of Patients. Following approval specific treatment services offered for rare malignancies such by our institutional review board, the NCDB was reviewed as sarcoma are unknown. Integrated network cancer pro- from 2004 to 2012. Created in 1989 by the American College grams usually have a “unified cancer committee” and consist of Surgeons (ACS) and the Commission on Cancer (CoC), of “multiple facilities providing comprehensive services” the NCDB captures 70% of all new United States cancer [15]. Academic institutions are defined with the same patient diagnoses and collects data from over 1,500 cancer centers volume definition as a comprehensive cancer center but also [12]. +e methodology for reporting to the NCDB has been have a noted resident/medical education program. previously described [8]. Adult patients (≥18 years old) with bone sarcoma diagnosed between 2004 and 2012 were identified using topographical codes (C40.0-C40.3, C40.8- 2.3. Statistical Analysis. +e number of patients and fre- C41.4, C41.8, C41.9) designated by International Classifi- quencies for all independent categorical variables were re- ported. Median TTI was reported given the nonparametric cation of Disease for Oncology, +ird Edition [ICD-O-3]. A patient also required an ICD-O-3 histology code consistent dataset and was compared across different levels of the same categorical variable by using Kruskal-Wallis tests. +e re- with a bone sarcoma to be included. +ese codes identified a total of 13,329 patients with a bone sarcoma. Patients were lationship between OS and TTI, along with other important excluded for the following reasons: (1) lack of follow-up or secondary covariates such as age, gender, race, and treatment essential data (n � 1,485), (2) American Joint Committee on modality were examined with Cox regression modeling. Cancer (AJCC) Stage IV or unknown stage disease Hazard ratios (HR) and 95% confidence intervals (CI) were (n � 5,686), and (3) well differentiated (grade 1), moderately determined for each variable. +e TTI variable was entered differentiated (grade 2), or unknown grade (n � 4,036). +us, into the full Cox regression by using four-knot restricted cubic splines to allow for a nonlinear relationship between 2,122 adult patients with localized, high-grade disease were included in the final analysis. Given the significant impact TTI and the survival outcome [16]. However, the spline effect was not significant. Given the nonsignificant and tumor grade and disease stage have been shown to have on survival outcome [9, 13, 14], this cohort was intentionally nonlinear relationship of TTI with survival in all TTI Sarcoma 3 Table 1: Continued. 13,329 patients identified Factor Total (N � 2,122) Transition in care 1,485 with missing data No 1,137 (53.6%) Excluded 5,686 with stage IV or Yes 985 (46.4%) unknown disease Year of diagnosis 2004 160 (7.5%) 4,036 with grades 1, 2 or unknow grade 2005 213 (10.0%) 2006 226 (10.7%) 2,122 patients included in 2007 202 (9.5%) analysis 2008 244 (11.5%) 2009 273 (12.9%) Figure 1: Study cohort inclusion criteria. 2010 274 (12.9%) 2011 267 (12.6%) 2012 263 (12.4%) Primary tumor site Table 1: Demographic data. Upper extremity 281 (13.2%) Lower extremity 985 (46.4%) Factor Total (N � 2,122) Pelvis 344 (16.2%) Time to treatment initiation, days (IQR) 25.0 [12.0, 42.0] Other 512 (24.1%) Age Tumor size 18–30 654 (30.8%) ≤8.0 cm 967 (45.6%) 31–50 555 (26.2%) >8.0 cm 1,155 (54.4%) 51–70 627 (29.5%) Grade 71+ 286 (13.5%) Poorly differentiated 1,253 (59.0%) Sex Undifferentiated 869 (41.0%) Male 1,241 (58.5%) Clinical staging Female 881 (41.5%) Stage I 239 (11.3%) Race Stage II 1,782 (84.0%) White 1,735 (81.8%) Stage III 101 (4.8%) Black 258 (12.2%) First-line treatment modality Other/unknown 129 (6.1%) Surgery 1,029 (48.5%) Charlson/Deyo score Radiation 86 (4.1%) 0 1,843 (86.9%) Systemic 994 (46.8%) 1 222 (10.5%) Multimodal 13 (0.61%) ≥2 57 (2.7%) Vital status Histology Died 922 (43.4%) Osteosarcoma 1,217 (57.4%) Alive 1,200 (56.6%) Chondrosarcoma 486 (22.9%) Statistics presented as median [P25, P75] or N (column %). Community Ewing’s sarcoma 195 (9.2%) cancer program: between 100 and 500 new cancer cases annually, Com- Chordoma 17 (0.80%) prehensive community cancer program: >500 new cancer cases annually, Other 207 (9.8%) academic center: >500 new cancer cases annually and resident/medical Facility type education, integrated network: multiple facilities providing comprehensive Comm. cancer prg. 38 (1.8%) services with a unified cancer committee. comm., community; prg., Comprehensive comm. cancer prg. 286 (13.5%) program. Academic center 856 (40.3%) Integrated network cancer prg. 62 (2.9%) Other/unknown 880 (41.5%) cohorts, cubic spline modeling of HR according to TTI as a Insurance continuous variable was not performed. After specifying Uninsured 120 (5.7%) different TTI values (TTI � 14, 30, 60, 90, and 150 days) and Private insurance 1,148 (54.1%) by setting the covariates to their reference levels, the 1-year, Medicaid 258 (12.2%) 5-year, and 10-year survival probabilities were determined Medicare 454 (21.4%) and associated survival curves were plotted. Statistical an- Other/unknown 142 (6.7%) alyses were completed with SAS software (Version 9.4; Cary, Income NC). +e multivariable cox regression model was built using <$38,000 404 (19.0%) rms package in R software (Version 3.4; Vienna, Austria). $38,000-$47,999 500 (23.6%) $48,000-$62,999 563 (26.5%) All tests were two-sided, with an alpha level of 0.05. P values $63,000+ 655 (30.9%) less than 0.05 were considered significant. Distance from facility <21 miles 974 (45.9%) 3. Results 21–50 miles 466 (22.0%) 51–100 miles 306 (14.4%) 3.1. TTI and Survival. Overall survival probabilities dem- >100 miles 376 (17.7%) onstrated minimal differences at 1 year, 5 years, and 10 years 4 Sarcoma Table 2: 1-year, 5-year, and 10-year survival probabilities based at TTI � 14, 30, 60, 90, and 150 days (Table 2). Similarly, upon time to treatment initiation. adjusted survival curves generated by Cox regression modeling were near identical out to 10 years (HR � 1.00; Time Survival probability 95% CI P � 0.72) (Figure 2). TTI � 14 1 year 0.84 0.74 0.95 5 years 0.46 0.26 0.79 3.2. Factors 3at Influence Survival. Univariate analysis 10 years 0.36 0.18 0.74 revealed significant differences seen in regard to the rela- TTI � 30 tionship of TTI with several secondary variables (Table 3). 1 year 0.84 0.74 0.95 Multivariable analysis also identified several secondary pa- 5 years 0.46 0.26 0.79 tient, tumor, treatment, and healthcare system related fac- 10 years 0.36 0.18 0.74 TTI � 60 tors associated with mortality (Table 4). +ose that were 1 year 0.84 0.74 0.95 statistically significant are highlighted in Figure 3. Patient 5 years 0.46 0.27 0.80 factors such as age between 51 and 70 (HR = 1.66; P � 0.004) 10 years 0.37 0.18 0.75 and age of 71+ (HR = 2.89; P< 0.001) and patients with a TTI � 90 Charlson/Deyo score ≥2 (HR = 2.02; P< 0.001) were asso- 1 year 0.84 0.75 0.95 ciated with decreased survival, whereas sex, race, and income 5 years 0.46 0.27 0.80 were not associated with survival. A diagnosis of chon- 10 years 0.37 0.18 0.75 drosarcoma (HR = 0.75; P � 0.002), chordoma (HR = 0.27; TTI � 150 P � 0.01), or other bone sarcoma not including Ewing’s 1 year 0.85 0.75 0.96 sarcoma (HR = 0.75; P � 0.022) all were associated with 5 years 0.47 0.27 0.82 increased survival when compared to osteosarcoma, whereas 10 years 0.38 0.18 0.78 tumors located in the pelvis (HR = 1.58; P< 0.001) and TTI: time to treatment initiation; CI: confidence interval. tumors greater than 8 cm in size (HR = 1.52; P< 0.001) were associated with decreased survival. Being a distance between 1.0 51 and 100 miles from the treatment center (HR = 1.30; P � 0.012) compared to being less than 21 miles away was associated with decreased survival, though being greater 0.8 than 100 miles away had no effect. Any year of diagnosis between 2005 and 2012 compared to 2004 did not influence 0.6 prognosis. Patients treated at an academic center (HR = 0.64; P � 0.039) or other noncategorized center (HR = 0.50; 0.4 P � 0.006) compared to a community cancer program had an association with increased survival. Patients with private insurance (HR = 0.65; P � 0.004) or Medicare insurance 0.2 (HR = 0.71; P � 0.043) had an association with increased survival. Having a transition in care after diagnosis to an- 0.0 other center for treatment did not influence survival out- 0 12 24 36 48 60 72 84 96 108 120 132 come (HR = 0.90; P � 0.14). First-line treatment of radiation Months therapy (HR = 1.81; P< 0.001) when compared to surgery as first treatment had an association with decreased survival. 14 90 Tumor grade and clinical stage did not demonstrate asso- 30 150 ciation with survival, as to be expected in a cohort of only high grade, localized bone sarcomas. Figure 2: Survival curves using different values for time to treatment initiation. +is graph demonstrates the near-identical Kaplan–Meier survival curves when comparing patients with a time 4. Discussion to treatment initiation of 14, 30, 60, 90, and 150 days (HR � 1.00; P � 0.72). +ese data demonstrate that all cause survival probability at one, five, and ten years after diagnosis was no different when comparing patients with a TTI ranging from 0 to 150 days outcome in their cohort of extremity osteosarcomas. In both breast and head and neck cancers, recent registry data have (five months). Factors found to correlate with survival in- cluded patient age, comorbidity index, histologic subtype, shown a correlation between increased treatment wait times primary tumor location and size, initial treatment type, type and decreased survival [4, 5]. Nevertheless, given the of insurance, treating facility type, and distance of home findings of the present study and previous work in soft tissue residence from the treating facility. sarcoma [7], it remains unclear as to why TTI has little Prior data associating treatment delay with survival prognostic implication in sarcoma. outcome in sarcoma is limited, with only a single study that Far more studied is the association between time to compared a treatment delay of less than or greater than three diagnosis and survival, as delay in diagnosis is the most weeks [9]. +e authors concluded no difference on survival common reason for litigation related to the treatment of Survival probability Sarcoma 5 Table 3: Univariate relationships between factors and time to treatment initiation. Factor N TTI, days median [p25, p75] P value Age 0.006 18–30 654 21.0 [13.0, 366.0] 31–50 555 28.0 [14.0, 44.0] 51–70 627 26.0 [12.0, 45.0] 71+ 286 25.5 [7.0, 44.0] Sex 0.52 Male 1241 24.0 [12.0, 42.0] Female 881 26.0 [13.0, 43.0] Race 0.050 White 1735 25.0 [12.0, 42.0] Black 258 28.0 [22.0, 48.0] Other/unknown 129 20.0 [7.0, 44.0] Charlson/Deyo score 0.18 0 1843 25.0 [13.0, 42.0] 1 258 22.0 [9.0, 40.0] ≥2 57 29.0[7.0, 44.0] Histology 0.003 Osteosarcoma 1217 25.0 [13.0, 40.0] Chondrosarcoma 486 27.0 [10.0, 48.0] Ewing’s sarcoma 195 21.0 [11.0, 34.0] Chordoma 17 38.0 [17.0, 77.0] Other 207 29.0 [15.0, 49.0] Facility type <0.001 Comm. cancer prg. 38 32.5 [1.00, 48.0] Comprehensive comm. cancer Prg. 286 21.5 [5.0, 40.0] Academic center 856 27.0 [14.0, 47.0] Integrated network cancer program 62 29.5 [11.0, 52.0] Other/unknown 880 23.0 [13.0, 37.0] Insurance <0.001 Uninsured 120 27.5 [15.0, 43.5] Private insurance 1148 23.0 [12.0, 39.0] Medicaid 258 26.0 [13.0, 43.0] Medicare 454 27.5 [10.0, 48.0] Other/unknown 142 35.0 [19.0, 52.0] Income 0.73 <$38,000 404 25.5 [12.0, 45.5] $38,000–$47,999 500 24.0 [12.0, 40.5] $48,000–$62,999 563 24.0 [11.0, 43.0] $63,000+ 655 26.0 [14.0, 42.0] Distance from facility 0.069 >21 miles 974 25.0 [12.0, 42.0] 21–50 miles 466 24.0 [13.0, 42.0] 51–100 miles 306 23.0 [9.0, 40.0] >100 miles 376 28.0 [14.5, 44.0] Transition in care <0.001 No 1137 20.0 [8.0, 35.0] Yes 985 31.0 [19.0, 49.0] Year of diagnosis 0.25 2004 160 25.5 [9.0, 42.0] 2005 213 27.0 [14.0, 51.0] 2006 226 24.0 [11.0, 39.0] 2007 202 25.5 [13.0, 43.0] 2008 244 25.0 [13.0, 42.0] 2009 273 23.0 [11.0, 39.0] 2010 274 25.5 [14.0, 41.0] 2011 267 27.0 [14.0, 44.0] 2012 263 25.0 [12.0, 42.0] Primary tumor site <0.001 Upper extremity 281 25.0 [14.0, 42.0] Lower extremity 985 22.0 [12.0, 36.0] 6 Sarcoma Table 3: Continued. Factor N TTI, days median [p25, p75] P value Pelvis 344 29.0 [15.0, 49.0] Other 512 28.0 [9.5, 48.0] Tumor size 0.48 ≤8.0 cm 967 26.0 [12.0, 42.0] >8.0 cm 1155 25.0 [13.0, 42.0] Grade 0.63 Poorly differentiated 1253 25.0 [11.0, 43.0] Undifferentiated 869 26.0 [14.0, 42.0] Clinical staging 0.10 Stage I 239 28.0 [14.0, 49.0] Stage II 1782 24.0 [12.0, 42.0] Stage III 101 27.0 [11.0, 45.0] First-line treatment modality <0.001 Surgery 1029 24.0 [6.0, 47.0] Radiation 86 34.5 [19.0, 56.0] Systemic 994 25.0 [15.0, 37.0] Multimodel 13 39.0 [26.0, 47.0] P values correspond to the Kruskal–Wallis test. Comm.: community; prg.: program; TTI: time to treatment initiation. extremity sarcoma [17]. +e traditional legal argument is therapy first, as we suspect this cohort was likely biased toward unresectable tumors or patients undergoing pallia- that the increased time allows for a cancer to grow and spread, leading to worse prognosis. Prior studies have tion. Furthermore, patients who lived a distance of 51–100 evaluated the length of time prior to diagnosis (or duration miles from the treatment center compared to those who of symptoms) in bone sarcoma and have demonstrated no lived <21 miles away had an increased risk of death, despite significant correlation with survival [13, 14]. +is infor- having a shorter median TTI (23 days vs. 25 days, respec- mation is useful when counseling patients who exhibit re- tively). To no surprise, insured status (private insurer or morse or anxiety for not presenting to a physician sooner. Medicare insurer) when compared to being uninsured was Considering the lack of correlation between longer duration found to be associated with increased survival, similar to of symptoms and worsened survival, it is perhaps not recently reported trends seen in prostate, lung, and colo- surprising that TTI (which is typically a much shorter time rectal cancer [18]. Furthermore, our data supported the period than time to diagnosis, 3 weeks [8] vs. 16 weeks [13]), previously noted correlation between receiving care at a high-volume facility and improved survival outcome similarly found no difference. Factors rooted in tumor bi- ology, outside the control of the treating team, are likely a [7, 19, 20]. As well, a transition in care, which previously has powerful confounding factor in understanding the natural been shown to have the greatest correlation with longer TTI history of primary bone sarcoma. [8], was not associated with a survival disadvantage. +is In a 2019 analysis utilizing the NCDB population, supports the concept of referral to a sarcoma referral center Lawrenz et al. identified patient and disease-specific factors with a multidisciplinary treatment team, despite the likely that correlated with TTI in over 13,000 patients with bone delay in treatment initiation. sarcoma, highlighting transitions in care from one treating +is study has several limitations. A retrospective facility to another as being responsible for the greatest in- analysis utilizing multivariable regression only allows for determination of correlation between factors and an out- creases in TTI [8]. Other factors associated with longer TTI included uninsured or government insurer status, nonwhite come, not causation. We recognize there are factors not included in our analysis which remain unaccounted for or race, pelvic tumor location, and treatment at an academic center. A secondary aim of this study was to identify patient, uncontrolled. To this end, we sought to reduce the potential tumor, and healthcare system factors associated with sur- confounding effect of severity of disease and its known vival. Understanding the overwhelming influence tumor strong correlation with prognosis by restricting this cohort grade and disease stage have been shown to have on to only patients with localized, high-grade disease. Despite prognosis [9, 13, 14], this cohort was intentionally limited to this, we recognize this cohort of bone sarcomas consists of patients with high grade, localized disease. Similar to prior multiple histology types, in which there can be differences work, this data reiterates that increased patient age (>51 amongst individual types on prognosis, which may blunt the years), increased tumor size (>8 cm), and pelvic tumor lo- effect of treatment delay in the cohort as a whole. Fur- thermore, national registries are prone to incomplete data cation are correlated with decreased survival, and a diagnosis of chondrosarcoma or chordoma are correlated with in- reporting and even unknown data collection errors. In this dataset, there were 1,485 patients missing time to treatment creased survival [13]. It was not surprising to learn that patients who underwent radiation therapy as first treatment data which we excluded. As well, 40% of patients were (86 patients, 4.1%) had an associated worse prognosis categorized as “other/unknown treatment facility type.” compared to patients who underwent surgery or systemic Given that this was not a critical factor in assessing our Sarcoma 7 Table 4: Multivariate analysis of factors associated with survival. 95% Hazard Factors hazard P values ratio ratio CI TTI—a 10-day increase from day 14 1.00 0.98 1.02 0.72 TTI—a 10-day increase from day 30 1.00 0.98 1.02 0.72 Time to treatments, days TTI—a 10-day increase from day 60 1.00 0.98 1.02 0.72 TTI—a 10-day increase from day 90 1.00 0.98 1.02 0.72 TTI—a 10-day increase from day 150 1.00 0.98 1.02 0.72 31–50 vs. 18–30 1.16 0.88 1.51 0.29 Age group, years 51–70 vs. 18–30 1.66 1.17 2.34 0.004 71+ vs. 18–30 2.89 1.95 4.28 <0.001 Sex Female vs. male 0.94 0.82 1.07 0.33 Black vs. white 0.94 0.75 1.17 0.59 Race Other/unknown vs. white 0.98 0.73 1.31 0.88 1 vs. 0 1.11 0.90 1.36 0.34 Charlson/Deyo score ≥2 vs. 0 2.02 1.45 2.81 <0.001 $38,000–$47,999 vs. <$38,000 1.08 0.88 1.33 0.45 Income $48,000–$62,999 vs. <$38,000 1.03 0.84 1.27 0.75 $63,000+ vs. <$38,000 1.04 0.84 1.29 0.70 Private insurance vs. uninsured 0.65 0.49 0.87 0.004 Medicaid vs. uninsured 0.85 0.61 1.18 0.33 Insurance Medicare vs. uninsured 0.71 0.51 0.99 0.043 Other/unknown vs. uninsured 0.75 0.51 1.10 0.15 Comprehensive community cancer program vs. community cancer 0.89 0.58 1.39 0.62 program Facility type Academic center vs. community cancer program 0.64 0.41 0.98 0.039 Integrated network cancer program vs. community cancer program 0.99 0.58 1.68 0.97 Other/unknown vs. community cancer program 0.50 0.30 0.82 0.006 21–50 miles vs. <21 miles 1.17 0.98 1.39 0.088 Distance from facility 51–100 miles vs. <21 miles 1.30 1.06 1.59 0.012 >100 miles vs. <21 miles 1.08 0.88 1.33 0.44 Transition in care Yes vs. No 0.90 0.78 1.04 0.14 2005 vs. 2004 1.06 0.79 1.41 0.71 2006 vs. 2004 0.84 0.63 1.13 0.26 2007 vs. 2004 1.18 0.88 1.58 0.27 2008 vs. 2004 0.84 0.62 1.13 0.25 Year of diagnosis 2009 vs. 2004 0.90 0.67 1.21 0.48 2010 vs. 2004 1.00 0.74 1.35 0.99 2011 vs. 2004 1.22 0.90 1.65 0.19 2012 vs. 2004 1.06 0.76 1.47 0.73 Radiation vs. surgery 1.81 1.35 2.42 <0.001 First-line treatment Systemic vs. surgery 1.17 0.99 1.39 0.06 modality Multimodal vs. surgery 0.60 0.24 1.49 0.27 Chondrosarcoma vs. osteosarcoma 0.75 0.62 0.90 0.002 Ewing’s sarcoma vs. osteosarcoma 0.82 0.62 1.09 0.17 Histology Chordoma vs. osteosarcoma 0.27 0.10 0.73 0.01 Other vs. osteosarcoma 0.75 0.59 0.96 0.022 Lower extremity vs. upper extremity 0.92 0.75 1.13 0.42 Primary tumor site Pelvis vs. upper extremity 1.58 1.26 1.99 <0.001 Other vs. upper extremity 1.05 0.83 1.32 0.70 Tumor size >8.0 cm vs. ≤8.0 cm 1.52 1.32 1.76 <0.001 Grade Undifferentiated vs. poorly differentiated 1.07 0.94 1.23 0.31 Stage II vs. stage I 0.96 0.77 1.20 0.72 Clinical staging Stage III vs. stage I 0.97 0.69 1.38 0.87 TTI: time to treatment initiation; CI: confidence interval. primary endpoint, we included these patients for the sake of when studying a rare disease such as sarcoma, tools such as increased sample size, though making conclusions regarding the NCDB though imperfect provide a large cohort to in- this specific variable more difficult to interpret. Despite this, vestigate important questions for the purposes of data 8 Sarcoma Age > 71 2.89 Charloson/Deyo score ≥ 2 2.02 Radiation therapy 1.81 Age 51–70 1.66 Pelvic tumor site 1.58 Tumor size > 8 cm 1.52 Distance 51–100 miles 1.3 Chondrosarcoma 0.75 Other PBS diagnosis 0.75 Medicare insurance 0.71 Private insurance 0.65 Academic center 0.64 Other/unknown center 0.5 Chordoma 0.27 Hazard ratio Figure 3: Comparison of relative association between covariates and survival. Only covariates with statistically significant higher (red) or lower (green) HR are shown. description and hypothesis generation. +ese limitations rather than the length of time from when a diagnosis is made could be largely improved upon with a multi-institutional and when treatment is initiated. +is is important in coun- prospective registry effort focused on sarcoma diagnoses. seling patients, who may delay treatment to receive a second In conclusion, this analysis of the NCDB from 2004 to opinion or seek referral to a higher volume sarcoma center. 2012 demonstrates TTI does not correlate with overall sur- vival in localized, high-grade primary bone sarcoma in adults. Data Availability +e primary and secondary conclusions of this data suggest that factors inherent to the patient, disease process, and +e data used to support the findings of this study are in- treating facility are likely more integral to overall prognosis, cluded within the article. Covariate Sarcoma 9 [16] A. Jemal, R. C. Tiwari, T. Murray et al., “Cancer statistics, Conflicts of Interest 2004,” CA: A Cancer Journal for Clinicians, vol. 54, no. 1, pp. 8–29, 2004. +e authors declare that there are no conflicts of interest [17] N. W. Mesko, J. L. Mesko, L. M. Gaffney, J. L. Halpern, related to this work. H. S. Schwartz, and G. E. Holt, “Medical malpractice and sarcoma care-a thirty-three year review of case resolutions, References inciting factors, and at risk physician specialties surrounding a rare diagnosis,” Journal of Surgical Oncology, vol. 110, no. 8, [1] N. Howlader, A. Noone, and M. Krapcho, SEER Cancer pp. 919–929, 2014. Statistics Review, National Cancer Institute, Bethesda, MD, [18] L. Ellis, A. J. Canchola, D. Spiegel, U. Ladabaum, R. Haile, and USA, 2017. S. L. Gomez, “Trends in cancer survival by health insurance [2] R. J. Grimer, “Size matters for sarcomas!” 3e Annals of 3e status in California from 1997 to 2014,” JAMA Oncology, Royal College of Surgeons of England, vol. 88, no. 6, vol. 4, no. 3, pp. 317–323, 2018. pp. 519–524, 2006. [19] J. C. Gutierrez, E. A. Perez, F. L. Moffat, A. S. Livingstone, [3] R. J. Grimer and T. W. R. Briggs, “Earlier diagnosis of bone D. Franceschi, and L. G. Koniaris, “Should soft tissue sar- and soft-tissue tumours,” 3e Journal of Bone and Joint comas be treated at high-volume centers?” Annals of Surgery, Surgery. British Volume, vol. 92, no. 11, pp. 1489–1492, 2010. vol. 245, no. 6, pp. 952–958, 2007. [4] R. J. Bleicher, K. Ruth, E. R. Sigurdson et al., “Time to surgery [20] A. L. Lazarides, D. L. Kerr, D. P. Nussbaum et al., “Soft tissue and breast cancer survival in the United States,” JAMA On- sarcoma of the extremities,” Clinical Orthopaedics and Related cology, vol. 2, no. 3, pp. 330–339, 2016. Research, vol. 477, no. 4, pp. 718–727, 2019. [5] C. T. Murphy, T. J. Galloway, E. A. Handorf et al., “Survival impact of increasing time to treatment initiation for patients with head and neck cancer in the United States,” Journal of Clinical Oncology, vol. 34, no. 2, pp. 169–178, 2016. [6] O. Zaikova, K. Sundby Hall, E. Styring et al., “Referral pat- terns, treatment and outcome of high-grade malignant bone sarcoma in Scandinavia-SSG Central Register 25 years’ ex- perience,” Journal of Surgical Oncology, vol. 112, no. 8, pp. 853–860, 2015. [7] J. Featherall, G. L. Curtis, J. M. Lawrenz et al., “Time to treatment initiation and survival in adult localized, high-grade soft tissue sarcoma,” Journal of Surgical Oncology, vol. 120, no. 7, pp. 1241–1251, 2019. [8] J. M. Lawrenz, G. L. Curtis, J. F. Styron et al., “Adult primary bone sarcoma and time to treatment initiation: an analysis of the National Cancer Database,” Sarcoma, vol. 2018, Article ID 1728302, 9 pages, 2018. [9] S. S. Bielack, B. Kempf-Bielack, G. Delling et al., “Prognostic factors in high-grade osteosarcoma of the extremities or trunk: an analysis of 1,702 patients treated on neoadjuvant cooperative osteosarcoma study group protocols,” Journal of Clinical Oncology, vol. 20, no. 3, pp. 776–790, 2002. [10] T. A. Damron, W. G. Ward, and A. Stewart, “Osteosarcoma, chondrosarcoma, and Ewing’s sarcoma,” Clinical Orthopae- dics and Related Research, vol. 459, pp. 40–47, 2007. [11] C. T. Murphy, T. J. Galloway, E. A. Handorf et al., “Increasing time to treatment initiation for head and neck cancer: an analysis of the National Cancer Database,” Cancer, vol. 121, no. 8, pp. 1204–1213, 2015. [12] S. Mohanty and K. Y. Bilimoria, “Comparing national cancer registries: the National Cancer Data Base (NCDB) and the surveillance, epidemiology, and end results (SEER) program,” Journal of Surgical Oncology, vol. 109, no. 7, pp. 629-630, 2014. [13] J. M. Lawrenz, J. F. Styron, M. Parry, R. J. Grimer, and N. W. Mesko, “Longer duration of symptoms at the time of presentation is not associated with worse survival in primary bone sarcoma,” 3e Bone & Joint Journal, vol. 100, no. 5, pp. 652–661, 2018. [14] B. T. Rougraff, K. Davis, and J. Lawrence, “Does length of symptoms before diagnosis of sarcoma affect patient sur- vival?” Clinical Orthopaedics and Related Research, vol. 462, pp. 181–189, 2007. [15] National Cancer Data Base—Data Dictionary PUF, 2014.

Journal

SarcomaHindawi Publishing Corporation

Published: May 5, 2020

References