Access the full text.
Sign up today, get DeepDyve free for 14 days.
Abstract Outcomes research typically assesses three major health care outcomes, including quantity of life, quality of life (QOL), and health care cost. This article highlights the impact of treatment-associated mucositis on health care costs and QOL. After a background description of the economic analyses of overall cancer treatment costs and of the incremental costs associated with other treatment side effects, data from a retrospective study of mucositis-specific costs are presented. The second half of this article reviews current knowledge about the effect that mucositis has on QOL. Because the empirical work that specifically evaluates mucositis and QOL is quite limited, studies examining proxies for mucositis grading are described. These include studies comparing the QOL of patients currently undergoing treatment, in which symptoms likely to be associated with mucositis are worse, with that of patients who have completed treatment. Also discussed are investigations examining both the relationship between specific mucositis-associated symptoms, such as pain and difficulty swallowing, and QOL and the weighting of different domains of mucositis-associated problems. Finally, several future research directions are suggested, with the intent of expanding knowledge about the economic and QOL impact of mucositis in patients treated for head and neck cancer. [J Natl Cancer Inst Monogr 2001;29:45–51] With the increasing use of aggressive chemotherapy and/or radiation therapy protocols to treat head and neck cancer, attention to the consequences of the major treatment side effect, mucositis, is clearly warranted. This article will highlight the impact of mucositis on health care costs and quality of life (QOL). Economic Costs of Mucositis Economists divide the economic costs of illness into three basic categories. These categories include direct costs, which can be both medical (e.g., hospital admissions and prescription medications) and nonmedical (e.g., transportation and health care supplies); indirect costs such as lost wages from time away from work; and intangible costs, which are largely psychosocial in nature (1). Economic analyses are regularly included in clinical trials (2), and the analyses typically examine all direct medical costs associated with a particular treatment. The absolute costs of two treatments can then be compared. In addition, a cost-effectiveness ratio, or the ratio of economic costs to effectiveness or value, may be calculated. Economic cost comparisons of different treatment modalities for head and neck cancer have been conducted. For example, Myers et al. (3) evaluated three potential treatments for stage T1 glottic larynx cancer: microlaryngoscopy, radiation therapy, and hemilaryngectomy. The results indicated that microlaryngoscopy had the lowest cost, followed by radiation therapy, with hemilaryngectomy being the most expensive. In a cost-effectiveness analysis examining actual costs, not charges, for treatment of stage I or II glottic cancer, Foote et al. (4) demonstrated that the costs of transoral endoscopic removal were lower than those of radiation therapy and partial vertical laryngectomy. However, the cost-effectiveness portion of the analysis attempted to take into account incidence of local recurrence and voice quality: The inclusion of these factors, which the authors judged to be superior in the radiation therapy group, led to the conclusion that radiation therapy may provide the best value for a moderate incremental cost. Other investigators (5,6) have examined the relationship of particular diagnostic and staging procedures to treatment costs, including positron emission tomography scans and fine-needle aspiration biopsies. Sherman et al. (7) provided a recent review of economic analyses in head and neck cancer, including the methodologic challenges inherent in conducting such investigations with a very heterogeneous population. Less common are evaluations of the economic costs of a particular treatment side effect, i.e., an evaluation of the costs associated with managing a particular symptom, such as mucositis, that arises as a consequence of cancer treatment. Such incremental costs are those attributable to mucositis over and above those attributable to the cancer and its treatment. While there appear to be no published investigations of the costs of treating mucositis in head and neck cancer, the incremental costs associated with the treatment of other toxic effects have been examined—most notably, febrile neutropenia and nausea/vomiting. For example, McQuaker et al. (8) evaluated the use of filgrastim in patients who had received a stem cell transplant. The authors identified several major costs potentially associated with neutropenia, including intravenous antibiotic therapy, days with fever, and number and cost of inpatient hospital days. In a randomized trial of filgrastim versus placebo, they demonstrated that the economic costs in the filgrastim group were statistically significantly lower than those in the placebo group, based on the identified cost items. A somewhat similar method was used by Stewart et al. (9) in their investigation of the costs of preventing and treating nausea and vomiting in patients receiving highly emetogenic chemotherapy. Specific inpatient and outpatient resources were enumerated, including those for different antiemetic drugs; supplies; nursing, physician, and pharmacist time; and outpatient and inpatient hospital visits/stays. The cost associated with each resource was then specified. Finally, costs were calculated for patients receiving ondansetron as opposed to other antiemetic regimens. Results strongly favored ondansetron, with statistically significantly lower economic costs primarily because of fewer inpatient stays for gastrointestinal complications. In summary, evaluations of economic costs and cost-effectiveness of cancer treatments have become increasingly more common, although little of this work has been done in head and neck cancer. Investigations typically target either the overall costs associated with a particular cancer treatment or the specific costs believed to be associated with a treatment side effect. In light of the prevalence and severity of mucositis in patients treated for head and neck cancer and the lack of information on the incremental economic costs associated with it, we recently evaluated the direct medical costs associated with mucositis management. The study consisted of three parts. First, a focus group of physician and nurse experts in head and neck cancer treatment met to identify the potential resources used in the management of mucositis. Second, a retrospective chart review was conducted in a consecutive sample of 45 patients treated with radiation therapy or combined chemoradiotherapy for head and neck cancer at a single institution. Resources specifically aimed at mucositis management were identified for each patient throughout the course of his or her treatment. Finally, we utilized two costing methodologies to derive monetary cost estimates for the mucositis management resources used. The focus group consisted of two physicians (one radiation oncologist and one medical oncologist) and two nurses, all of whom had at least 3 years' experience treating head and neck cancer patients. They identified five categories of resource use for mucositis management that would account for incremental direct medical costs. These resources were primarily directed at managing pain and nutritional/hydration consequences and included hospitalization for dehydration, malnourishment, or pain; additional professional time spent by physicians, nurses, and nutritionists in mucositis management; maintenance of appropriate nutritional and hydration status, such as placement of gastrostomy tubes, intravenous (IV) hydration, and nutritional supplements; prescription medications for pain and other mouth care; and home health assistance when needed for tube feedings and IV hydration. We then reviewed the charts of a consecutive series of patients treated with radiation therapy or with chemoradiotherapy protocols for head and neck cancer at a single institution from May 1994 through December 1996. Subjects were eligible if they received their complete course of cancer treatment at this institution, so that necessary records were available for review, and if they had not received previous radiation therapy or chemotherapy for head and neck cancer. Charts of the 45 patients who met these eligibility criteria were reviewed, and data on basic demographic, disease, and treatment information; number of visits to health care personnel; hospitalizations during treatment; the use of prescription medications, nutritional supplements, and IV hydration; and mucositis severity throughout treatment were recorded for the period beginning with the start of treatment and ending with the date 2 months after the end of treatment, at which time most of the treatment-related mucositis had remitted. One research assistant reviewed all records, and 10% of the records were also reviewed by the first author. The interrater agreement on coding was calculated to be an acceptable 85%. The main area of nonagreement was in the number of professional visits, and this appeared to be attributable to the multiple sections of the charts where visits could be recorded (i.e., progress notes, treatment log, flow sheet). The noted discrepancies were corrected through rereview of the pertinent charts. The median age of the subjects was 59.3 years (range, 33–87 years). The subjects were mostly male (66.7%) and European-American (65.1%), with a range of disease severity (stage I: 14.3%; stage II: 16.7%; stage III: 26.2%; and stage IV: 42.9%). Fifty-six percent were treated with radiation therapy only, while 13% were treated with alternating chemotherapy and radiation therapy, and 31% were treated with concurrent chemotherapy and radiation therapy. Tables 1 and 2 show the mucositis-associated resources used by this sample of patients. Table 1 demonstrates that roughly one third of the patients had substantial nutritional or hydration support needs, 15.6% of which were severe enough to require hospitalization for dehydration. Table 1 also displays professional time and the portion of this time calculated to be incremental to the management of mucositis. That is, for the resource-use categories other than professional time, all resources were assumed to be incremental to mucositis (i.e., it is assumed that the need for pain medication or IV hydration resulted directly from the presence and severity of mucositis). Professional time, however, differs in that some nurse and physician visits would be a regular part of patient care during head and neck cancer treatment, while others might be extra visits occasioned by mucositis-associated problems. Because the reason for each professional visit was not available in this retrospective review, we had to make an assumption that subjects with more severe mucositis would have more professional visits prompted by the side effects than would those with less severe mucositis. We calculated incremental professional time by subtracting the mean number of visits for those with less severe (grades 0 or 1) mucositis from the mean number for those with more severe (grades 2–4) mucositis. The drawback of this assumption is that it assigns all extra visits to mucositis, although subjects with more severe mucositis also had other more severe problems or side effects that might have occasioned the additional professional visits. Thus, this may be an overestimate of the incremental professional time specifically prompted by mucositis. Finally, the relatively common use of narcotic and nonnarcotic pain relievers and antifungal medications is shown in Table 2. The third step in this study was to assign a dollar value to the opportunity cost of the resource-use categories. Because true cost data are quite difficult to obtain, we used charges and reimbursements as proxies for actual costs. Specifically, we determined low and high estimates of charges/reimbursements for each of the categories. This allowed us to compare the results of two different costing methodologies. For hospitalizations, professional time, and outpatient hydration, Medicare reimbursements were used as the low estimate, and the charges billed by the hospital oncology unit were used as the high estimate. Low and high estimates for nutritional supplements came from a local pharmacy chain price and a hospital-based pharmacy price, respectively. Wholesale and retail prices from the 1996 Drug Topics Red Book (10) formed the low and high estimates for prescription medications, while values for the nutritionist time were calculated on the basis of charges for minimal (basic) versus extensive (complicated) visits. The low and high incremental cost estimates for each resource-use category can be found in Table 3. Note that, as would be expected, hospitalizations add the largest amount to mean total incremental cost ($1840–$1966). Outpatient support ($534–$828) and prescription medication ($452–$1049) have intermediate costs. The cost of incremental professional time is relatively low ($122–$194). Standard deviations are quite large for all category estimates, revealing the strikingly wide variability of mucositis-related costs in this sample. Finally, we examined whether costs differed between subjects who differed in the degree of severity of the mucositis that developed during treatment. For these analyses, patients were categorized as having either low-severity (grade 0 or 1) or high-severity (grades 2 – 4) mucositis based on the most severe grade mentioned in the treatment notes. Wilcoxon rank-sum tests were used to test for differences in costs as a function of mucositis severity. At both low and high estimates of costs, the group with more severe mucositis had statistically significantly greater costs in two of the four cost categories, including outpatient nutrition/hydration support (low: z = 2.06, P = .04; high: z = 2.22, P = .03) and prescription medications (low: z = 3.23, P = .001; high: z = 3.51. P = .0005). The cost owing to hospitalization did not differ statistically significantly by mucositis severity at either the low (z = 1.59, ns [not statistically significant]) or high (z = 1.59, ns) estimates of cost. However, the mean differences were quite large, with a difference of $1331 at the low cost estimate and $1522 at the high cost estimate. It is likely that the lack of statistically significant difference can be attributed to the very large standard deviations of the estimates. Because incremental professional time was defined as the additional increment of time spent with patients with more severe mucositis, it was not possible to calculate a z score for incremental professional time. Total cost estimates did differ between mucositis severity groups at both low (z = 2.82, P = .005) and high (z = 3.07, P = .0021) cost estimates. The results of this study must be considered in light of the following limitations, which were largely a result of the retrospective nature of the study. First, there was not a standard mucositis grading system in use when the data were collected. Thus, variability in the application of a single grading system across providers or across grading systems may have introduced unmeasured error into the results comparing costs between those with low-grade mucositis and those with high-grade mucositis. Second, it was not always possible to ascertain whether a hospitalization for rehydration was needed because of mucositis or because of chemotherapy-induced nausea/vomiting. We made the assumption that all such hospitalizations could be attributed to mucositis. Thus, the estimate of the cost of inpatient care for hydration might be somewhat inflated. Finally, it should be noted that the large standard deviations of the cost estimates might lessen confidence in their accuracy. Further work is clearly needed to address these study limitations. In summary, despite the constraints imposed by the retrospective nature of this study, the findings indicate that mucositis has statistically significant direct medical costs (approximately $3000 ± $1000 per treatment episode) and that these costs are greater for patients experiencing more severe mucositis. A similar type of methodology could be used in a prospective study to provide a more precise estimate of both resource use and associated costs across the course of treatment. Mucositis and Quality of Life Health-related QOL “refers to the extent to which one's usual or expected physical, emotional and social well-being are affected by a medical condition or its treatment” (11). The two key aspects of QOL are that it is subjective and multidimensional (12–14). Regarding subjectivity, the field of QOL very clearly emphasizes the centrality of the patient's perspective. The judgments and comparisons between current and expected functioning that make up one's QOL are complex (15) and cannot easily be inferred from outside. QOL measures typically assess at least four dimensions, including physical, emotional, social, and functional well-being. In brief, physical well-being refers to perceived bodily function or dysfunction, including the level of physical symptoms; emotional well-being includes both positive mood, such as hope and joy, and negative mood, such as depression and anxiety; social well-being is the ability to maintain important social relationships and a feeling of being supported by others; and functional well-being is the ability to perform and enjoy normal daily activities. Other investigators have emphasized additional QOL dimensions, including sexuality (16) and spirituality (17). Total health-related (global) QOL, then, is an aggregation of a number of individual dimensions. It has been demonstrated that physical and psychological symptoms and/or side effects have a statistically significant impact on the various QOL dimensions (18,19). In our work, we found a strong linear relationship between severity of symptoms, rated from “not at all” to “very much,” and scores on individual dimensions of, and total, QOL. Symptoms/side effects evaluated in this sample of 1163 patients with mixed cancer types included pain, trouble sleeping, weakness, nausea, diarrhea, tension, worry, irritability, and depression (18). The fact that findings across a variety of symptoms and toxic effects were similar lends credence to the exploration of the QOL impact of another important side effect: mucositis. One way to begin to examine the relationship between mucositis and QOL is to consider its possible consequences and how they may affect each of the major QOL dimensions. Thus, major factors associated with mucositis include pain, difficulty swallowing, impaired ability to eat and drink, substantial time needed for complex mouth care regimens, and impaired ability to speak and communicate (20,21). Pain and difficulty swallowing are symptoms that can be considered to be part of physical well-being. Impairment in eating/drinking and speaking/communicating are functional problems that may also have sizable effects on one's social well-being. That is, meals are often social gatherings, and an inability to participate fully in them may negatively affect feelings about relationships with others. Speech problems and the potential need to find alternative methods of communication for a period of time also likely serve to decrease the ability to participate in social interactions and derive pleasure from them. The requirement to perform complex mouth care regimens may also be considered to be a functional impairment, since it takes away time and energy that could otherwise be devoted to more enjoyable daily activities. These consequences, separately or in total, may have a substantial impact on emotional well-being as well. That is, sadness, tension, or feelings of isolation and loss of self-identity can result from physical symptoms, impaired functioning, and decreased social interaction. Although to date no specific instruments have been created to measure the QOL impact of mucositis, there are several well-validated QOL questionnaires for patients with head and neck cancer; all include questions that address possible mucositis-related impairments. Two questionnaires specifically address the functional abilities, or performance status, that may be affected by head and neck cancer and its treatment. These include the List Performance Status Scale for Head and Neck Cancer (PSS-HN) (22) and the University of Washington QOL questionnaire (UWQOL) (23). The PSS-HN is a clinician-rated instrument that consists of three subscales assessing normalcy of diet, understandability of speech, and eating in public. Dysfunction in these three areas is rated on a scale from 0% to 100%, with higher scores indicating fewer problems. The UWQOL is a nine-item scale on which patients rate the level of difficulty experienced in areas such as pain, disfigurement, activity, eating, employment, and speech. Two other questionnaires widely used to evaluate QOL in head and neck cancer are the European Organization for Research and Treatment of Cancer QLQ-C30 + Head and Neck Module (24) and the Functional Assessment of Cancer Therapy— Head and Neck Cancer Scale (FACT-H&N) (25). Both are composed of a general questionnaire assessing the major QOL dimensions discussed above and an additional subscale addressing head and neck cancer-specific problems that are not contained in the general questionnaire (e.g., “I have pain” could assess mucositis-related pain but is included in the physical well-being subscale and so is not included in the additional concerns subscale). For example, the FACT-H&N contains 27 items assessing physical, social/family, emotional, and functional well-being and an 11-item head and neck cancer subscale. Subscale items are shown in Table 4. Two strengths of this type of general plus specific questionnaire are the potential to calculate a total (general + head and neck cancer specific) QOL score and the possibility of examining the relationship between head and neck cancer-specific concerns and the other QOL dimensions. For example, it would be possible to evaluate whether those with greater head and neck cancer-specific problems also report more impairment in functional or social well-being. In general, there is a high degree of concordance between head and neck cancer-specific scales, such as the PSS-HN, the UWQOL, and the FACT-H&N subscale, with a lesser association between head and neck cancer-specific scales and the general QOL scales of the FACT-H&N; this suggests an additional perspective that can be gained on patients' QOL by using both general and disease-specific instruments (26). As can be seen by examining the questions of the disease-specific scales, about half of the questions address concerns that might be specifically related to mucositis (e.g., ability to eat and communicate, swallowing, and voice quality on the FACT-H&N subscale). However, previous surgery and the disease itself are other potential causes of these symptoms. Mucositis is widely acknowledged as a consequence of high-dose chemotherapy (27–29), radiation therapy (21,30,31), and the multimodal treatment regimens used to treat head and neck cancer (32–34). A number of studies (20,21,29–31,34–36) have commented that mucositis adversely affects patients' QOL but have not done so in the context of an empirical investigation of QOL. In the absence of empirical data, another way to evaluate the importance of mucositis to QOL is to compare QOL scores of those on chemotherapy or radiation treatment, who are, therefore, likely to be experiencing mucositis, with patients not currently receiving treatment. A number of authors have examined this question (25,37–43). In a series of three studies, List et al. (25,37,38) evaluated treatment-related symptoms and QOL. In a cross-sectional comparison, List et al. (25) demonstrated that patients undergoing treatment reported greater head and neck cancer-specific concerns as well as poorer physical, functional, and total well-being. List et al. (37) also investigated a cross-sectional sample of patients with head and neck cancer (stages II–IV) 1 year after completion of an intensive chemoradiotherapy protocol. Although 70% of this sample experienced mucositis of grade 3 or 4 during treatment, this experience was not long lasting and was not related to their experience of residual pain or eating difficulties 1 year later. Residual mouth and throat pain were, however, related to QOL 1 year after treatment. Subsequently, List et al. (38) conducted a longitudinal study examining QOL in a sample of patients before, during, and after concomitant chemotherapy/radiation treatment. In the comparison of head and neck cancer-specific concerns before and during treatment, there was greater impairment during treatment in almost all areas. Thus, a greater percentage of patients on chemotherapy/radiation treatment reported problems in global functioning, normalcy of diet, and speech on the PSS-HN (22) and were more likely to report such specific symptoms as difficulty swallowing, mouth and throat pain, and hoarse voice. In those patients who survived at least 1 year after treatment, improvements were reported in global functioning, normalcy of diet, swallowing difficulties, and throat pain. Speech, mouth pain, and hoarse voice were not statistically significantly improved from reports during treatment. Scores on the FACT-H&N indicated only an improvement in physical well-being from treatment to 1 year after treatment. These results suggest that mucositis related to chemotherapy and radiation treatment may substantially impair performance status and QOL but that there are other important disease- and treatment-related factors to be considered as well. Using a very detailed and specific evaluation of the side effects of radiation therapy, Trotti et al. (39) found statistically significant increases from pretreatment to 4 weeks into radiation therapy in the following areas: pain in throat, difficulty swallowing breads/meats and liquids, changes in mucous and saliva, changes in taste, difficulty chewing, and speech difficulties. The only potential mucositis-related symptom not to increase over that 4-week period was pain in the mouth. In addition, there was a very strong correlation (.85) between the total score for these specific symptoms and a general QOL measure, highlighting their importance to overall well-being during treatment. In another investigation (40), QOL was assessed repeatedly throughout a sequential, multimodal protocol for the treatment of advanced head and neck cancer. Patients received either chemotherapy + surgery + radiation therapy or chemotherapy + radiation therapy only. The interesting results demonstrated a decrease in QOL from baseline to the second cycle of chemotherapy for all patients, poorer QOL in patients following surgery, and the worst QOL for both groups of patients during radiation therapy. Although this is a report of only a small number of patients, it demonstrates the utility of multiple, longitudinal QOL assessment and comparison between treatment arms. Several longitudinal studies have examined both short- and long-term QOL-related treatment effects. For example, both disease-specific QOL and general QOL were assessed before radiotherapy for laryngeal cancer, as well as 6 and 12 months after the therapy (41). There was a statistically significant increase in head and neck symptoms related to mucositis and fatigue and a decrease in physical functioning when comparing the baseline to the 6-month assessments. However, of interest is the finding that both emotional well-being and mood improved at the 6-month assessment. Thus, there is some discordance between the physical/functional and emotional domains of QOL at this time, when mucositis-associated symptoms appear to still be present. We note that this may suggest the importance of adaptive psychological processes: Better mood, even in the face of continuing symptoms, may also be a function of relief at the end of active cancer treatment. Pretreatment factors and type of treatment can also be predictive of post-treatment QOL and symptoms (42). Thus, a high level of depression and a low performance status at baseline and the receipt of combination therapy predicted increased symptom severity following the end of treatment. More intensive treatment was associated with greater head and neck cancer-specific symptomatology, while depression and performance status were better predictors of overall QOL. Finally, there has been at least one attempt to systematically examine the relative importance of different head and neck symptoms/treatment effects to global QOL (43). This type of work will be particularly important in comparing treatments that have different short- or long-term side effect profiles. Subjects had no evidence of disease and had completed treatment within the last 2–12 months. They filled out a survey examining speech, eating, aesthetics, pain/discomfort, social/role functioning, and global QOL. In univariate analyses, social/role functioning and speech had the strongest association with global QOL. In a logistic regression designed to examine the relative predictive ability of each of the domains, speech and eating were the best independent predictors of global QOL. Although this study included a relatively small number of subjects and, thus, clearly needs to be replicated in a large, representative sample, it does represent information that may be critically important to the evaluation of patient preferences for various treatment modalities. Conclusions and Recommendations for Future Research Research on the specific economic and QOL impact of mucositis, independent of other head and neck treatment/disease-related problems, is rather limited. Summary statements about the likely negative impact of mucositis abound in the head and neck cancer literature. The extant empirical work reviewed above provides apparently compelling support for these claims but is all based on inference. That is, the relationship between mucositis severity, specifically, and QOL was not reported in any of the investigations. Rather, it was necessary to make the assumption either that mucositis is more severe in those receiving treatment or that patients' reports of symptoms, such as pain and swallowing difficulty, are related to mucositis. While a logical and useful first step, our understanding of the specific QOL impact of mucositis would clearly be enhanced by a prospective longitudinal evaluation of mucositis severity, symptoms, functional status, and global- and head and neck cancer-specific QOL. Such studies would also allow us to explore the potentially complex relationship between physician-graded toxicity (mucositis), patient-reported specific symptom severity, and multiple domains of QOL. It will be particularly interesting to examine the way in which mucositis and related symptomatology, such as eating and communication difficulties, affect social well-being. Another important line of research will be that of evaluating patients' preferences for the potentially different acute and long-term consequences of increasingly aggressive treatment protocols. That is, careful explication of the QOL implications of different treatments (i.e., what it will really mean to a patient's sense of well-being in various areas) may inform treatment decision making, particularly in the absence of a clear survival advantage of one treatment versus another. List et al. (44) have demonstrated that, while cure and long-term survival are the most desired treatment outcomes, rankings of other outcomes, such as less pain and improved level of eating and communication ability, vary statistically significantly among patients. The provision of accurate information on short- and long-term treatment effects, such as mucositis and QOL, would help to address treatment-planning difficulty created by normal interpatient variability in preferences. Finally, a careful prospective evaluation of the economic costs associated with the management of mucositis would be useful. The methodology utilized in our retrospective study reported above, with resource identification and costing strategies, is similar to that used in prospective studies of the costs related to other treatment side effects. Such a prospective economic evaluation will be particularly helpful given the increasing evaluation of the clinical utility of protective methods, such as granulocyte colony-stimulating factors (45), that are designed to minimize mucositis during intensive head and neck cancer treatment. Cost-effectiveness or cost-benefit analyses could be conducted with knowledge of the true costs of mucositis management and the costs and efficacy of such protective agents. In summary, the rapid expansion of antineoplastic treatment regimens in head and neck cancer, the often dose-limiting toxicity of mucositis, the evaluation of new protective agents, and the substantial heterogeneity of patients' evaluation of symptoms and QOL make the continued evaluation of the QOL and economic impact of mucositis an important and exciting area of investigation. Table 1. Mucositis resource use (n = 45) Mean No. (SD) %/Range Hospitalization G-tube placed Yes 16 35.6% No 29 64.4% G-tube replaced because of complications Yes 3 6.7% No 42 93.3% Hospitalized for hydration Yes 7 15.6% No 38 84.4% Professional time Physician visits 11.4 (3.9) 5–229 Nurse visits 17.4 (8.8) 5–389 Incremental professional time Physician visits 3.0 (2.9) 0–129 Nurse visits 7.7 (7.9) 0–259 Outpatient support Nutritionist visits 3.2 (2.01) 0–797 Intravenous hydration Required 13 28.9% Not required 32 71.1% Total No. of liters required 2.8 (9.1) 0–549 Nutritional supplements Required 37 82.2% Not required 8 17.8% Total No. of cans of supplement 235.2 (255.2) 0–973 Mean No. (SD) %/Range Hospitalization G-tube placed Yes 16 35.6% No 29 64.4% G-tube replaced because of complications Yes 3 6.7% No 42 93.3% Hospitalized for hydration Yes 7 15.6% No 38 84.4% Professional time Physician visits 11.4 (3.9) 5–229 Nurse visits 17.4 (8.8) 5–389 Incremental professional time Physician visits 3.0 (2.9) 0–129 Nurse visits 7.7 (7.9) 0–259 Outpatient support Nutritionist visits 3.2 (2.01) 0–797 Intravenous hydration Required 13 28.9% Not required 32 71.1% Total No. of liters required 2.8 (9.1) 0–549 Nutritional supplements Required 37 82.2% Not required 8 17.8% Total No. of cans of supplement 235.2 (255.2) 0–973 View Large Table 2. Prescription drug usage (n = 45) Prescription drug Not prescribed One course prescribed* Two courses prescribed Three courses prescribed *One course assumed to be 1 month for all medications except Diflucan, for which one course is 7 days. Advil™ 41 4 0 0 Diflucan™ 34 6 2 3 Dilaudid™ 44 1 0 0 Duragesic/Fentanyl™ patch 40 4 1 0 MS Contin™ 44 1 0 0 Mycelex™ 43 2 0 0 Nystatin™ 37 7 1 0 Peridex™ 43 1 1 0 Roxanol™ 33 9 3 0 Salagen™ 40 4 1 0 Stomatitis cocktail™ 23 17 4 1 Trilisate™ 31 11 2 1 Tylenol 3™ 20 18 5 2 Tylenol 4™ 44 1 0 0 Vicodin™ 38 6 0 1 Prescription drug Not prescribed One course prescribed* Two courses prescribed Three courses prescribed *One course assumed to be 1 month for all medications except Diflucan, for which one course is 7 days. Advil™ 41 4 0 0 Diflucan™ 34 6 2 3 Dilaudid™ 44 1 0 0 Duragesic/Fentanyl™ patch 40 4 1 0 MS Contin™ 44 1 0 0 Mycelex™ 43 2 0 0 Nystatin™ 37 7 1 0 Peridex™ 43 1 1 0 Roxanol™ 33 9 3 0 Salagen™ 40 4 1 0 Stomatitis cocktail™ 23 17 4 1 Trilisate™ 31 11 2 1 Tylenol 3™ 20 18 5 2 Tylenol 4™ 44 1 0 0 Vicodin™ 38 6 0 1 View Large Table 3. Estimates of incremental costs due to mucositis (n = 45)* Low cost High cost Cost category Mean/median (SD) Range Mean/median (SD) Range *SD = standard deviation. †Low and high cost estimates are significantly different using the Wilcoxon rank-sum test (P<.05). Incremental professional time $122/$32 (161) $0–$623 $194/$54 (257) $0–$992 Outpatient support† $534/$418 (432) $0–$2069 $828/$614 (810) $0–$4418 Prescription medications† $452/$329 (418) $0–$160 $1049/$508 (1190) $0–$4563 Hospitalizations $1840/$0 (2765) $0–$12 924 $1966/$0 (2945) $0–$13 675 Total costs† $2949/$1281 (3252) $0–$15 472 $4037/$2704 (4119) $0–$19 182 Low cost High cost Cost category Mean/median (SD) Range Mean/median (SD) Range *SD = standard deviation. †Low and high cost estimates are significantly different using the Wilcoxon rank-sum test (P<.05). Incremental professional time $122/$32 (161) $0–$623 $194/$54 (257) $0–$992 Outpatient support† $534/$418 (432) $0–$2069 $828/$614 (810) $0–$4418 Prescription medications† $452/$329 (418) $0–$160 $1049/$508 (1190) $0–$4563 Hospitalizations $1840/$0 (2765) $0–$12 924 $1966/$0 (2945) $0–$13 675 Total costs† $2949/$1281 (3252) $0–$15 472 $4037/$2704 (4119) $0–$19 182 View Large Table 4. Functional assessment of cancer therapy— head and neck cancer subscale items I am able to eat the foods that I like. My mouth is dry. I have trouble breathing. My voice has its usual quality and strength. I am able to eat as much food as I want. I am unhappy with how my face and neck look. I can swallow naturally and easily. I smoke cigarettes or other tobacco products. I drink alcohol (e.g., beer, wine, etc.). I am able to communicate with others. I can eat solid foods. I am able to eat the foods that I like. My mouth is dry. I have trouble breathing. My voice has its usual quality and strength. I am able to eat as much food as I want. I am unhappy with how my face and neck look. I can swallow naturally and easily. I smoke cigarettes or other tobacco products. I drink alcohol (e.g., beer, wine, etc.). I am able to communicate with others. I can eat solid foods. View Large Partially supported by Searle Pharmaceuticals, Inc. References 1 Gold M, Siegel J, Russell L, Weinstein M. Cost-effectiveness in health and medicine. New York (NY): Oxford University Press; 1996. Google Scholar 2 Bennett CL, Armitage JL, Buchner D, Gulati S. Economic analysis in phase III clinical cancer trials. Cancer Investig 1994; 12: 336–42. Google Scholar 3 Myers EN, Wagner RL, Johnson JT. Microlaryngoscopic surgery for T1 glottic lesions: a cost-effective option. Ann Otol Rhinol Laryngol 1994; 103: 28–30. Google Scholar 4 Foote RL, Buskirk SJ, Grado GL, Bonner JA. Has radiotherapy become too expensive to be considered a treatment option for early glottic cancer? Head Neck 1997; 19: 692–700. Google Scholar 5 Valk PE, Pounds TR, Tesar RD, Hopkins DM, Haseman MK. Cost-effectiveness of PET imaging in clinical oncology. Nucl Med Biol 1996; 23: 737–43. Google Scholar 6 Gharib H, Goellner HR. Fine needle aspiration biopsy of the thyroid: an appraisal. Ann Intern Med 1993; 118: 282–9. Google Scholar 7 Sherman EJ, Ruchlin HS, Holden JS, Pfister DG. Clinical economics of head and neck malignancies. Hematol Oncol Clin North Am 1999; 13: 867–81. Google Scholar 8 McQuaker IG, Hunter AE, Pacey S, Haynes AP, Igbal A, Russell NH. Low-dose filgrastim significantly enhances neutrophil recovery following autologous peripheral-blood stem-cell transplantation in patients with lymphoproliferative disorders: evidence for clinical and economic benefit. J Clin Oncol 1997; 15: 451–7. Google Scholar 9 Stewart DJ, Dahrouge S, Coyle D, Evans WK. Costs of treating and preventing nausea and vomiting in patients receiving chemotherapy. J Clin Oncol 1999; 17: 344–51. Google Scholar 10 Drug Topics Red Book. Montvale (NJ): Medical Economics Data; 1996. Google Scholar 11 Cella DF. Measuring quality of life in palliative care. Semin Oncol 1995; 22(2 Suppl 3): 73–81. Google Scholar 12 Aaronson NK. Quality of life: what is it? How should it be measured? Oncology 1988; 2: 69–74. Google Scholar 13 Cella DF. Quality of life: concepts and definitions. J Pain Symptom Manage 1994; 9: 186–92. Google Scholar 14 Schipper H, Clinch J, Powell V. Definitions and conceptual issues. In: Spilker B, editor. Quality of life assessment in clinical trials. New York (NY): Raven Press; 1990. p. 11–19. Google Scholar 15 Cella, DF, Cherin EA. Quality of life during and after cancer treatment. Comp Ther 1988; 4: 69–75. Google Scholar 16 Aaronson NK. Methodological issues in psychosocial oncology with specific reference to clinical trials. In: Ventafridda V, Vann Dam FS, Yancik R, Tamburini M, editors. Assessment of quality of life and cancer treatment. Amsterdam (The Netherlands): Elsevier; 1986. Google Scholar 17 Brady MJ, Peterman AH, Fitchett G, Mo M, Cella D. A case for including spirituality in quality of life measurement in oncology. Psycho-Oncology 1999; 8: 417–28. Google Scholar 18 Peterman AH, Chang C, Cella D. Mo M. Effect of symptom type and symptom intensity on multiple dimensions of quality of life. Presented at the International Society of Quality of Life Research 4th Annual Conference. Vienna, Austria. Quality Life Res 1997; 6: 696–7. Google Scholar 19 Portenoy RK, Thaler HT, Kornblith AB, Lepore JM, Friedlander-Klar H, Coyle N, et al. Symptom prevalence, characteristics and distress in a cancer population. Qual Life Res 1994; 3: 183–9. Google Scholar 20 Cengiz M, Ozyar E, Ozturk D, Akyol F, Atahan IL, Hayran M. Sucralfate in the prevention of radiation-induced oral mucositis. J Clin Gastroenterol 1999; 28: 40–3. Google Scholar 21 Franzen L, Henriksson R, Littbrand B, Zackrisson B. Effects of sucralfate on mucositis during and following radiotherapy of malignancies in the head and neck region. A double-blind placebo-controlled study. Acta Oncol 1995; 34: 219–23. Google Scholar 22 List MA, Ritter-Sterr CA, Lansky SB. A performance status scale for head and neck cancer patients. Cancer 1990; 66: 564–9. Google Scholar 23 Hassan SJ, Weymuller EA. Assessment of quality of life in head and neck cancer patients. Head Neck 1993; 15: 485–96. Google Scholar 24 Bjordol K, Hammerlid E, Ahlner-Elmquist M, deGraeff A, Boysen M, Evensen JF, et al. Quality of life in head and neck cancer patients: validation of the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire—H&N35. J Clin Oncol 1999; 17: 1008–19. Google Scholar 25 List MA, D'Antonio LL, Cella DF, Siston A, Mumby P, Haraf D, et al. The Performance Status Scale for Head and Neck Cancer Patients and the Functional Assessment of Cancer Therapy–Head and Neck Scale. A study of utility and validity. Cancer 1996; 77: 2294–301. Google Scholar 26 D'Antonio LL, Zimmerman GJ, Cella DF, Long SA. Quality of life and functional status measures in patients with head and neck cancer. Arch Otolaryngol Head Neck Surg 1996; 122: 482–7. Google Scholar 27 Bellm LA, Epstein JB, Rose-Ped A, Maratin P, Fuchs HJ. Patient reports of complications of bone marrow transplantation. Support Care Cancer 2000; 8: 33–9. Google Scholar 28 Epstein JB, Schubert MM. Oral mucositis in myelosuppressive cancer therapy. Oral Surg Oral Med Oral Pathol Oral Radiol Endod 1999; 88: 273–6. Google Scholar 29 Karthaus M, Rosenthal C, Ganser A. Prophylaxis and treatment of chemo- and radiotherapy-induced oral mucositis—are there new strategies? Bone Marrow Transplant 1999; 24: 1095–108. Google Scholar 30 Feber T. Management of mucositis in oral irradiation. Clin Oncol (R Coll Radiol) 1996; 8: 106–11. Google Scholar 31 Peterson DE. Research advances in oral mucositis. Curr Opin Oncol 1999; 11: 261–6. Google Scholar 32 Aisner J, Hiponia D, Conley B, Jacobs M, Gray W, Belani CP. Combined modalities in the treatment of head and neck cancers. Semin Oncol 1995; 22(3 Suppl 6): 28–34. Google Scholar 33 Chougule PB, Akhtar MS, Akerley W, Ready N, Safran H, McRae R, et al. Chemoradiotherapy for advanced inoperable head and neck cancer: a phase II study. Semin Radiat Oncol 1999; 9(2 Suppl 1): 58–63. Google Scholar 34 Trotti A. Toxicity in head and neck cancer: a review of trends and issues. Int J Radiat Oncol Biol Phys 2000; 47: 1–12. Google Scholar 35 Jansma J, Vissink A, Spijkervet FK, Roodenburg JL, Panders AK, Vermey A, et al. Protocol for the prevention and treatment of oral sequelae resulting from head and neck radiation therapy. Cancer 1992; 70: 2171–80. Google Scholar 36 Raber-Durlacher JE. Current practices for management of oral mucositis in cancer patients. Support Care Cancer 1999; 7: 71–4. Google Scholar 37 List MA, Mumby P, Haraf D, Siston A, Mick R, McCracken E, et al. Performance and quality of life outcome in patients completing concomitant chemoradiotherapy protocols for head and neck cancer. Qual Life Res 1997; 6: 274–84. Google Scholar 38 List MA, Siston A, Haraf D, Schumm P, Kies M, Stenson K, et al. Quality of life and performance in advanced head and neck cancer patients on concomitant chemoradiotherapy: a prospective examination. J Clin Oncol 1999; 17: 1020–8. Google Scholar 39 Trotti A, Johnson DJ, Gwede C, Casey L, Sauder B, Cantor A, et al. Development of a head and neck companion module for the quality of life-radiation therapy instrument (QOL-RTI). Int J Radiat Oncol Biol Phys 1998; 42: 257–61. Google Scholar 40 McDonough EM, Varvares MA, Dunphy FR, Dunleavy T, Dunphy CH, Boyd JH. Changes in quality of life scores in a population of patients treated for squamous cell carcinoma of the head and neck. Head Neck 1996; 18: 487–93. Google Scholar 41 deGraeff A, deLeeuw RJ, Ros WJ, Hordijk GJ, Battermann JJ, Blijham GH, et al. A prospective study on quality of life of laryngeal cancer patients treated with radiotherapy. Head Neck 1999; 21: 291–6. Google Scholar 42 deGraeff A, deLeeuw JR, Ros WJ, Hordijk GJ, Blijham GH, Winnubst JA. Pretreatment factors predicting quality of life after treatment for head and neck cancer. Head Neck 2000; 22: 398–407. Google Scholar 43 Karnell LH, Funk GF, Hoffman HT. Assessing head and neck cancer patient outcome domains. Head Neck 2000; 22: 6–11. Google Scholar 44 List MA, Stracks J, Colangelo L, Butler P, Ganzenko N, Lundy D, et al. How do head and neck cancer patients prioritize treatment outcomes before initiating treatment? J Clin Oncol 2000; 18: 877–84. Google Scholar 45 Mascarin M, Franchin G, Minatel E, Gobitti C, Talamini R, DeMaria D, et al. The effect of granulocyte colony-stimulating factor on oral mucositis in head and neck cancer patients treated with hyperfractionated radiotherapy. Oral Oncol 1999; 35(2): 203–8. Google Scholar © Oxford University Press
JNCI Monographs – Oxford University Press
Published: Oct 1, 2001
Access the full text.
Sign up today, get DeepDyve free for 14 days.