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Clinical Investigations: CANCER |

Who Gets Chemotherapy for Metastatic Lung Cancer?* FREE TO VIEW

Craig C. Earle, MD, MSc; Laura N. Venditti, MSc; Peter J. Neumann, ScD; Richard D. Gelber, PhD; Milton C. Weinstein, PhD; Arnold L. Potosky, PhD; Jane C. Weeks, MD, MSc
Author and Funding Information

*From the Center for Outcomes and Policy Research, Department of Adult Oncology (Drs. Earle, Venditti, and Weeks), and the Department of Biostatistical Science (Dr. Gelber), Dana-Farber Cancer Institute, Boston, MA; the Program on the Economic Evaluation of Medical Technology, Center for Risk Analysis, Harvard School of Public Health (Drs. Neumann and Weinstein), Boston, MA; and the Applied Research Program, National Cancer Institute (Dr. Potosky), Bethesda, MD.

Correspondence to: Craig C. Earle, MD, MSc, Center for Outcomes and Policy Research, Dana-Farber Cancer Center, 44 Binney St, Boston, MA, 02115; e-mail: craig_earle@dfci.harvard.edu



Chest. 2000;117(5):1239-1246. doi:10.1378/chest.117.5.1239
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Published online

Study objectives: To determine the prevalence and factors associated with chemotherapy use in elderly patients presenting with advanced lung cancer.

Design: A retrospective cohort study using administrative data.

Setting and patients: We analyzed the medical bills for the 6,308 Medicare patients > 65 years old with diagnosed stage IV non-small cell lung cancer (NSCLC) in the 11 SEER (survival, epidemiology, and end results) regions between 1991 and 1993. The main outcome measure, chemotherapy administration, was identified by the relevant medical billing codes. Patient sociodemographic and disease characteristics were obtained from the SEER database and census data.

Results: Almost 22% of patients received chemotherapy at some time for their metastatic NSCLC. As expected, younger patients and those with fewer comorbid conditions were more likely to receive chemotherapy. However, several nonmedical factors, such as nonblack race, higher socioeconomic status, treatment in a teaching hospital, and living in the Seattle/Puget Sound or Los Angeles SEER regions, also significantly increased a patient’s likelihood of receiving chemotherapy.

Conclusion: Compared to previous reports, the prevalence of chemotherapy use for advanced NSCLC appears to be increasing. However, despite uniform health insurance coverage, there is wide variation in the utilization of palliative chemotherapy among Medicare patients, and nonmedical factors are strong predictors of whether a patient receives chemotherapy. While it is impossible to know the appropriate rate of usage, nonmedical factors should only influence a patient’s likelihood of receiving treatment if they reflect patient treatment preference. Research to further clarify the costs, benefits, and patient preferences for chemotherapy in this patient population is warranted in order to minimize the effect of nonmedical biases on management decisions.

Figures in this Article

Lung cancer is the leading cause of cancer death in North America. There are> 170,000 new cases in the United States each year,1and at least 40% of patients already have advanced, incurable, metastatic (stage IV) disease at the time of diagnosis.2Non-small cell lung cancer (NSCLC) is the dominant histology, responsible for 75 to 80% of all lung malignancies. Metastatic NSCLC patients have a median survival of only 24 weeks and a 1- year survival of 10 to 20%.3Palliative chemotherapy has been shown to impart modest survival gains, increasing median survival by about 11/2 months, and survival at 1 year from 5 to 15%.4However, these benefits come with nontrivial toxicity and expense, making the appropriate use of chemotherapy in advanced NSCLC controversial.56

Several groups have published guidelines on the management of metastatic NSCLC. The American Society of Clinical Oncology suggests that “chemotherapy . . . is appropriate for selected patients who have a good performance status.”7Similarly, Canadian guidelines state that “it is reasonable to offer cisplatin-based chemotherapy to medically suitable patients,”8and those from the National Comprehensive Cancer Network say that for “patients with stage IV disease and a good performance status (Eastern Cooperative Oncology Group 0, 1, or 2), chemotherapy may be of benefit.”9

These recommendations all endorse the judicious use of chemotherapy in advanced NSCLC, and all clearly state that the patient’s general medical condition is the prime consideration in making a treatment recommendation. However, little is known about the frequency of chemotherapy use in the United States, or whether its use is truly guided by patients’ medical conditions. Previous authors have reported a prevalence of use of < 5% in patients > 65 years old.1011 However, these analyses are at least a decade old, and were carried out in limited geographic regions. Therefore, we undertook this study to assess the prevalence of, and patient characteristics associated with chemotherapy use for stage IV NSCLC in a nationally representative cohort of the elderly Medicare population.

Data Sources

We studied patients from the 11 tumor registries participating in the SEER (surveillance, epidemiology, and end results) program of the National Cancer Institute: San Francisco/Oakland, CT, Detroit, HI, IA, NM, Seattle/Puget Sound, UT, Atlanta, San Jose/Monterey, and Los Angeles. These registries collect uniform information on all cancers diagnosed within their geographic regions, capturing about 97% of all incident cases in those areas.12The geographic areas covered by SEER areas contain approximately 14% of the American population,13and are demographically fairly representative.14 Disease-related data collected include the cancer site, stage, histology, date of diagnosis, and date and cause of the patient’s death. The registries also record patient sociodemographic characteristics such as age, sex, and race/ethnicity, and link census data on each patient’s census-tract or zip code of residence, including median and per capita income and wealth, educational levels, and racial mix.

The Health Care Financing Administration Medicare database includes files through 1994 for inpatient and outpatient care, physician and laboratory billings, as well as bills for home health and hospice care. Each patient in the SEER and Medicare databases has a unique case identification number that permits matching and merging of the different files. In this way, cases have been linked between the databases with a 94% match rate.15

Cohort Assembly

The study sample consisted of all Medicare-eligible patients> 65 years old residing in 1 of 11 SEER areas between March 1, 1991, and December 31, 1993, who received a diagnosis of stage IV NSCLC, as patients with conditions diagnosed in 1993 are the most recent with linked Medicare data. Thirteen percent of patients were excluded because they were enrolled in a health maintenance organization (HMO) at some time during the study period, and, therefore, did not have complete treatment information. Cases were also excluded if their Medicare entitlement was on the basis of disability or end-stage renal disease, if the dates of diagnosis and death differed by > 2 months in the SEER and Medicare databases, or if the lung cancer was first identified at the time of death or autopsy (∼1% of total cases). Because the median age at diagnosis for lung cancer in the SEER public use database is approximately 65 years, the Medicare-eligible patients represent about half of all cases in these regions.

Identification of Chemotherapy Use

SEER collects information on initial cancer-directed surgery and radiation, defined as those treatments applied within 4 months of diagnosis. However, the National Cancer Institute does not release chemotherapy treatment data, because outpatient chemotherapy usage may be missed by SEER chart abstractions.15 Therefore, we identified chemotherapy use from Medicare claims. The International Classification of Disease Version 9 (ICD-9) diagnostic code V58.1 and ICD-9 procedure code 9925, and the diagnosis-related groups code 410 for chemotherapy administration detected chemotherapy use in the inpatient setting. For the outpatient files and physician billing claims, Health Care Financing Administration Common Procedure Coding System codes for chemotherapy administration (Q0083-Q0085, J7150, or J8999-J999), Current Procedural Terminology codes 96400, 96408, 96410, 96412, 96414, and 96545, as well as the relevant revenue center codes (0331, 0332, and 0335) were also used where applicable. Patients were considered to have received chemotherapy if any of these codes were used at any time after the diagnosis of metastatic lung cancer. Because some patients had prior or subsequent diagnoses of other cancers for which they may have received chemotherapy, we repeated all analyses for the subgroup of patients for whom stage IV NSCLC was the only cancer diagnosis ever recorded. The findings in this subgroup were similar to those of the larger cohort, and thus are not reported.

Comorbidity Scoring

We calculated the Charlson comorbidity index1617 by examining the ICD-9 diagnostic codes recorded in months −1 to −13 before the diagnosis of lung cancer in each patient, following the method described by Deyo et al.18We also used outpatient bills to identify comorbidities, requiring a diagnosis to appear on at least two occasions separated by at least a month, as described by Klabunde,19 and applied the Charlson weights to each comorbidity. Cancer-related codes may inadvertently capture some of the initial diagnostic workup for lung cancer; therefore, the Charlson score was calculated excluding cancer-related diagnoses, again as suggested by Klabunde.19 To assess the impact of these analytic decisions, we conducted secondary analyses including cancer as a comorbidity in the Charlson score, using only inpatient bills to calculate the score, and analyzing the Charlson score as an ordered-categorical variable (scores grouped 0, 1, and ≥ 2) as other authors have done.16,1819 The results were the same with each analysis, so these latter results are not reported.

Definitions of Explanatory Variables

Patients were classified by age at diagnosis (65 to 74, 75 to 84, 85 to 94, and 95 to 104 years) and by race/ethnicity (non-Hispanic white, non-Hispanic black, Hispanic, Asian, or other). Region-specific socioeconomic quintiles were developed based on the availability of information, according to the following hierarchy: (1) race- and age-specific median household wealth by census tract (85.2% of patients); (2) unadjusted median household income by census tract (6.7%); (3) median household wealth by census tract (1.2%); and (4) median household wealth by zip code (6.3%). Consequently, 93.1% of patients were classified with census level data, while only 0.5% of patients were socioeconomically unclassifiable. Although lacking the precision of patient level data, the utility of census level socioeconimic classification has been previously validated.20

Dummy variables were created for each of the SEER registries, using the one with the median proportion of patients receiving chemotherapy (Atlanta) as the comparator. To test whether HMO penetration among lung cancer patients could explain geographic differences in chemotherapy usage, we repeated the analysis with the registry variables replaced by a variable grouping the registries into with high (Los Angeles, San Francisco/Oakland, HI), medium (San Jose/Monterey, NM, Seattle/Puget Sound), and low (CT, Detroit, IA, UT, Atlanta) proportions of patients enrolled in HMOs during the study period.

Patients were classified as having been treated at a teaching hospital if their record contained at least one bill from an institution with a medical school affiliation. Because it is not always clear whether an institution is a teaching hospital, we repeated the analysis using several alternative criteria such as hospitals employing at least one resident in an accredited residency program in the same year that the bill was generated, and required the encounter with the teaching hospital to be within a month of diagnosis. These definitions all yielded similar results, and consequently are not reported. Institutions managing high volumes of lung cancer patients had characteristics similar to teaching hospitals and are also not reported.

Statistical Methods

Univariate analyses were carried out comparing the sociodemographic features of patients included in the analysis with those excluded due to their HMO enrollment, patients who received chemotherapy with those who did not, and patients treated in teaching hospitals with those who were not. We used t tests for continuous variables, and χ2 analyses for categorical variables.

Based on the explanatory variables that were significantly associated with chemotherapy use, we constructed a multivariate logistic regression model to predict the likelihood of receiving chemotherapy. Significant variables were identified through stepwise elimination, and interaction terms between these variables were further investigated if they had a χ2 p < 0.10. Average predicted probabilities were calculated for each variable using the regression model with that variable omitted. To evaluate whether observation time could confound the likelihood of receiving chemotherapy, we incorporated survival time as a variable in the logistic regression analysis, and performed a “landmark analysis” restricted to only those patients who survived at least 1 month, long enough to have the opportunity to be considered for chemotherapy. All statistical analyses were performed with Statistical Analysis Software version 6.12 for UNIX, (SAS Institute; Cary NC).

Patient Characteristics

Table 1 shows the characteristics of the 6,308 patients meeting our eligibility criteria. The average patient age was 74.2 years, and almost two-thirds were men. The majority of patients (84%) were non-Hispanic white, with< 10% in each of the other racial groups. Eighty-five percent of patients lived in an urban setting. The Detroit registry contributed the most patients, followed by CT, IA, Seattle/Puget Sound, Los Angeles, and San Francisco/Oakland. The histologic diagnoses were mostly adenocarcinoma or squamous cell carcinoma, with no differences between treatment or eligibility groups. Chemotherapy was given to 21.5% of patients in the cohort. When the analysis was restricted to only those patients surviving at least 1 month, the proportion treated increased to 25.7%.

Twenty-one percent of the patients had at least one significant comorbid condition recorded in the year prior to their lung cancer diagnosis. Table 2 shows the prevalence of the various comorbidities that contribute to the Charlson index. COPD was the most common comorbid condition, affecting 11.5% of patients. This was followed by congestive heart failure, cerebrovascular disease, and diabetes. Comorbidity scores ranged from 0 to 10 out of a total possible of 27.

Associations With Chemotherapy Use

Both univariate (Fig 1 ) and multivariate (Table 3 ) analyses showed that age was inversely related to the likelihood of receiving chemotherapy (odds ratio [OR], 0.46 for each incremental decade of life; 95% confidence interval [CI], 0.41 to 0.51), and that each additional comorbid condition decreased the odds of receiving chemotherapy by 0.85 (95% CI, 0.79 to 0.92). Several nonmedical factors also emerged as important predictors. Figure 2 shows the unadjusted proportion of chemotherapy usage in different patient groups, as well as the adjusted proportion that would be otherwise expected based on the logistic regression model. African-American patients were less likely to receive chemotherapy than those of other races (OR, 0.70; 95% CI, 0.55 to 0.88), as were those of lower compared to higher socioeconomic status (OR, 1.07 for successive quintile from low to high; 95% CI, 1.02 to 1.12). There were no important differences in the landmark analysis when the analysis was limited to patients who survived at least 1 month; however, longer survival time was significantly associated with increased odds of receiving chemotherapy when it was incorporated into the regression as an explanatory variable. Furthermore, when survival time was considered, socioeconomic status was no longer a significant predictor of chemotherapy use.

Based on their other comorbidities, patients treated in a teaching setting would be predicted to receive chemotherapy slightly less often than those treated entirely in a community setting (21% vs 22%); however, they were actually treated more frequently (23% vs 19%; OR, 1.40; 95% CI, 1.23 to 1.60). Certain geographic locations were also associated with higher chemotherapy use, from a high of 27% in Seattle/Puget Sound and Los Angeles, to a low of 7% in UT. Again, this amount of variation could not be explained by other covariates (Fig 2). There were no important interactions between the explanatory variables. The amount of HMO penetration in a SEER area did not influence chemotherapy usage. Patients residing in urban settings were not more likely to receive chemotherapy, nor was there a time trend over the 3 years of the study.

This study, the first to use large population-based data sets to assess chemotherapy utilization in advanced lung cancer, produced several interesting findings. The 21.5% of Medicare patients with stage IV NSCLC receiving chemotherapy for their lung cancer indicates that chemotherapy use is increasing relative to the rates reported in older studies. However, despite the fact that all patients in our cohort had the same health insurance coverage, the use of chemotherapy was far from consistent for all beneficiaries. Guidelines uniformly single out a patient’s medical condition as the main factor requiring consideration in the decision to offer chemotherapy, yet we found that several nonmedical factors (race/ethnicity, socioeconomic status, geographic location, and treatment in a teaching hospital) significantly affect a patient’s likelihood of receiving treatment that included chemotherapy.

There is little recent information on the use of chemotherapy for metastatic NSCLC in the United States. Greenberg et al11,21 reported results indicating that < 6% of patients with a diagnosis of advanced NSCLC in New Hampshire and Vermont between 1973 and 1976 received chemotherapy. Smith et al10 noted that 4.2% of Medicare patients in Virginia with a diagnosis of advanced NSCLC between 1985 and 1989 were treated with chemotherapy. When Hillner et al22looked at younger patients in Virginia with diagnoses received between 1989 and 1991, they found that 18.8% of lung cancer patients received chemotherapy at some time during the course of their illness. The prevalence of chemotherapy use may be lower in other countries. For example, Kesson et al23, in a retrospective study, found that only 10% of patients in Glasgow, Scotland were treated with chemotherapy in 1991 and 1992. With respect to physician’s attitudes toward treatment, Raby et al24found that only 20% of Canadian physicians surveyed thought that treating advanced NSCLC with chemotherapy was worthwhile, and Crook et al25 in Great Britain reported that 11% of clinicians would recommend chemotherapy for appropriate patients, rising to 26% if the patient was < 50 years old.

Relative to these previously reported figures, our results suggest that chemotherapy utilization is increasing over time. This corresponds temporally to the publication of several positive randomized trials comparing chemotherapy with supportive care alone in metastatic NSCLC.2628 However, our finding of an almost fourfold geographic variation in the proportion of patients receiving chemotherapy underscores the dangers of trying to generalize practice patterns from studies done in a limited region. Moreover, these studies, as well as our analysis, all assessed practice that existed prior to the publication of a definitive meta-analysis that confirmed the survival benefits of cisplatin-based chemotherapy.4 Consequently, the proportion of patients receiving chemotherapy today may well be higher.

While the decision to use chemotherapy is a complex one that must be made on a patient-by-patient basis, the inverse relationships between advanced age and comorbidity, and chemotherapy use, was expected. Elderly patients less frequently meet standard physiologic criteria for treatment,29 and may be less likely to desire aggressive therapies.10,22,3036 Patients with metastatic NSCLC tend to have high levels of comorbidity due to concomitant smoking-related illness. It has been observed that patients with even moderately impaired ambulation, for example, have reduced survival and greatly increased toxicity from chemotherapy when compared to more mobile patients.89,33,37Although the number of comorbid conditions is not equivalent to functional status,38 it has been associated with the likelihood of receiving treatment in other cancers.33,39 Our ORs relating age and comorbidity to the likelihood of receiving intervention are very similar to those reported by Smith et al.10

The predicted levels of chemotherapy use shown in Figure 2 are interesting. Clearly, adjustment for medical factors does not account for the variation seen by race or geography. However, a large amount of the variation seen with socioeconomic status can be explained by other factors. This is why socioeconomic status was no longer a significant predictor when survival time was factored into the analysis. Still, at each end of the spectrum, the very poor received less treatment then would otherwise be expected, while the rich received more.

Practice variation can reflect the attitudes of physicians and/or patients. Recent data suggest that physicians can have sex and racial biases that significantly influence their treatment recommendations.40This could explain associations observed by us and others between female sex,4142 black race,32,4347 lower socioeconomic status,43,4749 community settings,50 and certain geographic locations,32,5155 and reduced access to and utilization of medical technologies for other medical conditions. Moreover, patients with these characteristics often have poorer clinical outcomes,5657 possibly as a consequence of decreased access to care.

There must be some caution in generalizing from our results. Linked SEER-Medicare data only captures patients > 65 years old, making us unable to comment on the practice patterns pertaining to younger patients. Chemotherapy identification relied largely on Medicare procedure codes, and there are indications that these may be underreported.15,5860 As well, methods for comorbidity adjustment are still undergoing validation, and our identification of patients treated in teaching hospitals did not ensure that the decision to use chemotherapy was made in an academic setting. Nine hundred ninety-five patients were excluded because they were enrolled in an HMO during part of the study. These patients tended to be from urban areas and to have a higher socioeconomic status than those included. There are some data suggesting that the practice patterns in HMOs can differ significantly from those in a fee-for-service setting.39,59,61 However, important differences are unlikely for these elderly lung cancer patients, as the HMO penetration in a region did not significantly affect the rate of chemotherapy use observed.

The use of palliative chemotherapy appears to be increasing. Chemotherapy or supportive care can be appropriate choices in different clinical situations, so the appropriate level of chemotherapy use cannot be known. However, unless they are markers for patient treatment preferences, nonmedical factors such as race, geographic location, socioeconomic status, or treatment setting should not significantly affect management recommendations. Research to further clarify the costs, benefits, and patient preferences for chemotherapy in this population is warranted in order to minimize the effect of nonmedical biases on treatment decisions.

Abbreviations: CI = confidence interval; HMO = health maintenance organization; ICD-9 = International Classification of Disease Version 9; NSCLC = non-small cell lung cancer; OR = odds ratio; SEER = survival, epidemiology, and end results

Dr. Earle is a Cancer Care Ontario Research Fellow.

Supported in part by National Institutes of Health grant CA 72663.

Table Graphic Jump Location
Table 1. Characteristics of the Study Population*
* 

Numbers may not add due to rounding.

 

Significant univariate difference (p < 0.05) between patients who received chemotherapy and those who did not.

Table Graphic Jump Location
Table 2. Comorbidities in the Study Population of Patients With Metastatic NSCLC
* 

Not used in the primary analysis.

Figure Jump LinkFigure 1. Relationship between medical factors and chemotherapy use for metastatic NSCLC.Grahic Jump Location
Table Graphic Jump Location
Table 3. Multiple Logistic Regression Analysis Predicting the Overall Odds of Chemotherapy Use for Metastatic NSCLC*
* 

SES = socioeconomic status.

 

Age: the odds of receiving chemotherapy with each incremental decade of life; Black: the odds of an African American receiving chemotherapy compared to a Non-Hispanic white person; SES: the odds of receiving chemotherapy with each incremental quintile in socioeconomic status; NM, Seattle/Puget Sound, UT, Los Angeles: the odds of receiving chemotherapy for someone living in the NM, Seattle/Puget Sound, UT, or Los Angeles SEER registry regions compared to someone living in Atlanta (the registry with the median rate of chemotherapy use); Charlson index: the odds of someone receiving chemotherapy with each additional comorbidity in the Charlson index; and Teaching: the odds of receiving chemotherapy if they received some of their care in a hospital that is affiliated with a medical school.

Figure Jump LinkFigure 2. Adjusted and unadjusted relationships between nonmedical factors and chemotherapy use for metastatic NSCLC. The black bars represent the unadjusted proportions of patients in each group who received chemotherapy. The gray bars are the average predicted probabilities adjusted for the other covarities in the regression model (Table 3). See Table 3 for abbreviation.Grahic Jump Location
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Guadagnoli, E, Hauptman, PJ, Ayanian, JZ, et al Variation in the use of cardiac procedures after acute myocardial infarction.N Engl J Med1995;333,573-578. [CrossRef] [PubMed]
 
Guadagnoli, E, Ayanian, JZ, Gibbons, G, et al The influence of race on the use of surgical procedures for treatment of peripheral vascular disease of the lower extremities.Arch Surg1995;130,381-386. [CrossRef] [PubMed]
 
Lu-Yao, GL, Greenberg, ER Changes in prostate cancer incidence and treatment in USA.Lancet1994;343,251-254. [CrossRef] [PubMed]
 
Weeks, J, Pfister, DG Outcomes research studies.Oncology1996;10(11 Suppl),29-34
 
Epstein, AM, Stern, RS, Tognetti, J, et al The association of patients’ socioeconomic characteristics with the length of hospital stay and hospital charges within diagnosis-related groups.N Engl J Med1988;318,1579-1585. [CrossRef] [PubMed]
 
Dayal, HH, Polissar, L, Dahlbert, S Race, socioeconomic status, and other prognostic factors for survival from prostate cancer.J Natl Cancer Inst1985;74,1001-1006. [PubMed]
 
Whittle, J, Steinberg, EP, Anderson, GF, et al Accuracy of Medicare claims data for estimation of cancer incidence and resection rates among elderly Americans.Med Care1991;29,1226-1236. [CrossRef] [PubMed]
 
Riley, GF, Potosky, AL, Klabunde, CN, et al Stage at diagnosis and treatment patterns among older women with breast cancer: an HMO and fee-for-service comparison.JAMA1999;281,720-726. [CrossRef] [PubMed]
 
Frey, CM, McMillen, MM, Cowan, CD, et al Representativeness of the Surveillance, Epidemiology, and End Results program data: recent trends in cancer mortality rates.J Natl Cancer Inst1992;84,872-877. [CrossRef] [PubMed]
 
Riley, GF, Potosky, AL, Lubitz, JD, et al Stage of cancer at diagnosis for Medicare HMO and fee-for-service enrollees.Am J Public Health1994;84,1598-1604. [CrossRef] [PubMed]
 

Figures

Figure Jump LinkFigure 1. Relationship between medical factors and chemotherapy use for metastatic NSCLC.Grahic Jump Location
Figure Jump LinkFigure 2. Adjusted and unadjusted relationships between nonmedical factors and chemotherapy use for metastatic NSCLC. The black bars represent the unadjusted proportions of patients in each group who received chemotherapy. The gray bars are the average predicted probabilities adjusted for the other covarities in the regression model (Table 3). See Table 3 for abbreviation.Grahic Jump Location

Tables

Table Graphic Jump Location
Table 1. Characteristics of the Study Population*
* 

Numbers may not add due to rounding.

 

Significant univariate difference (p < 0.05) between patients who received chemotherapy and those who did not.

Table Graphic Jump Location
Table 2. Comorbidities in the Study Population of Patients With Metastatic NSCLC
* 

Not used in the primary analysis.

Table Graphic Jump Location
Table 3. Multiple Logistic Regression Analysis Predicting the Overall Odds of Chemotherapy Use for Metastatic NSCLC*
* 

SES = socioeconomic status.

 

Age: the odds of receiving chemotherapy with each incremental decade of life; Black: the odds of an African American receiving chemotherapy compared to a Non-Hispanic white person; SES: the odds of receiving chemotherapy with each incremental quintile in socioeconomic status; NM, Seattle/Puget Sound, UT, Los Angeles: the odds of receiving chemotherapy for someone living in the NM, Seattle/Puget Sound, UT, or Los Angeles SEER registry regions compared to someone living in Atlanta (the registry with the median rate of chemotherapy use); Charlson index: the odds of someone receiving chemotherapy with each additional comorbidity in the Charlson index; and Teaching: the odds of receiving chemotherapy if they received some of their care in a hospital that is affiliated with a medical school.

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Guadagnoli, E, Ayanian, JZ, Gibbons, G, et al The influence of race on the use of surgical procedures for treatment of peripheral vascular disease of the lower extremities.Arch Surg1995;130,381-386. [CrossRef] [PubMed]
 
Lu-Yao, GL, Greenberg, ER Changes in prostate cancer incidence and treatment in USA.Lancet1994;343,251-254. [CrossRef] [PubMed]
 
Weeks, J, Pfister, DG Outcomes research studies.Oncology1996;10(11 Suppl),29-34
 
Epstein, AM, Stern, RS, Tognetti, J, et al The association of patients’ socioeconomic characteristics with the length of hospital stay and hospital charges within diagnosis-related groups.N Engl J Med1988;318,1579-1585. [CrossRef] [PubMed]
 
Dayal, HH, Polissar, L, Dahlbert, S Race, socioeconomic status, and other prognostic factors for survival from prostate cancer.J Natl Cancer Inst1985;74,1001-1006. [PubMed]
 
Whittle, J, Steinberg, EP, Anderson, GF, et al Accuracy of Medicare claims data for estimation of cancer incidence and resection rates among elderly Americans.Med Care1991;29,1226-1236. [CrossRef] [PubMed]
 
Riley, GF, Potosky, AL, Klabunde, CN, et al Stage at diagnosis and treatment patterns among older women with breast cancer: an HMO and fee-for-service comparison.JAMA1999;281,720-726. [CrossRef] [PubMed]
 
Frey, CM, McMillen, MM, Cowan, CD, et al Representativeness of the Surveillance, Epidemiology, and End Results program data: recent trends in cancer mortality rates.J Natl Cancer Inst1992;84,872-877. [CrossRef] [PubMed]
 
Riley, GF, Potosky, AL, Lubitz, JD, et al Stage of cancer at diagnosis for Medicare HMO and fee-for-service enrollees.Am J Public Health1994;84,1598-1604. [CrossRef] [PubMed]
 
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