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Participation of Patients 65 Years of Age or Older in Cancer Clinical Trials

Joy H. Lewis, Meredith L. Kilgore, Dana P. Goldman, Edward L. Trimble, Richard Kaplan, Michael J. Montello, Michael G. Housman, José J. Escarce

From RAND Health, Santa Monica; the University of California Los Angeles and the West Los Angeles Veterans Affairs Medical Center, Los Angeles, CA; and the National Institutes of Health, National Cancer Institute, Bethesda, MD.

Address reprint requests to Joy H. Lewis, DO, RAND, 1700 Main St, Santa Monica, CA 90407-2138; email: jhs{at}ucla.edu.

	ABSTRACT

TOP ABSTRACT INTRODUCTION PATIENTS AND METHODS RESULTS DISCUSSION APPENDIX 1. APPENDIX 2. APPENDIX 3: REFERENCES

 
Purpose: Although 61% of new cases of cancer occur among the elderly, recent studies indicate that the elderly comprise only 25% of participants in cancer clinical trials. Further investigation into the reasons for low elderly participation is warranted. Our objective was to evaluate the participation of the elderly in clinical trials sponsored by the National Cancer Institute (NCI) and assess the impact of protocol exclusion criteria on elderly participation.

Patients and Methods: We conducted a retrospective analysis using NCI data, analyzing patient and trial characteristics for 59,300 patients enrolled onto 495 NCI-sponsored, cooperative group trials, active from 1997 through 2000. Our main outcome measure was the proportion of elderly patients enrolled onto cancer clinical trials compared with the proportion of incident cancer patients who are elderly.

Results: Overall, 32% of participants in phase II and III clinical trials were elderly, compared with 61% of patients with incident cancers in the United States who are elderly. The degree of underrepresentation was more pronounced in trials for early-stage cancers than in trials for late-stage cancers (P < .001). Furthermore, protocol exclusion criteria on the basis of organ-system abnormalities and functional status limitations were associated with lower elderly participation. We estimate that if protocol exclusions were relaxed, elderly participation in cancer trials would be 60%.

Conclusion: The elderly are underrepresented in cancer clinical trials relative to their disease burden. Older patients are more likely to have medical histories that make them ineligible for clinical trials because of protocol exclusions. Insurance coverage for clinical trials is one step toward improvement of elderly access to clinical trials. Without a change in study design or requirements, this step may not be sufficient.

	INTRODUCTION

TOP ABSTRACT INTRODUCTION PATIENTS AND METHODS RESULTS DISCUSSION APPENDIX 1. APPENDIX 2. APPENDIX 3: REFERENCES

 
CANCER WAS second only to heart disease as a leading cause of death in 1999.¹ The elderly (people aged 65 years or older) account for 61% of all new cancer cases and 70% of all cancer deaths,² and it is estimated that they have 11 times the cancer risk of people under the age of 65 years.² By 2030, approximately 20% of the United States population will be aged 65 years or older.³ Consequently, cancer care will become increasingly important.

Patients with cancer are living longer and experiencing better quality of life as a result of advances in cancer care. Clinical studies have resulted in curative treatments for leukemias, lymphomas, and germ cell tumors and decreased morbidity and mortality from colorectal and breast cancer.^4,5 Other studies have found better ways of caring for cancer patients, minimizing side effects, and reducing invasive procedures.^6,7 It is important that cancer clinical trials enroll a representative sample of patients to ensure that the results of these trials are applicable to all those with cancer.

Federal laws require that cancer trials enroll representative samples of women and members of minority groups.^8–11 These laws may have had some success; several studies indicate that women and minorities are proportionately enrolled onto National Cancer Institute (NCI)-sponsored, cooperative group treatment trials,^12–14 whereas other studies disagree.¹⁵ In contrast, research indicates that the elderly are underrepresented in cancer clinical trials.^15–18

A study of Southwest Oncology Group clinical trials active between 1993 and 1996 found that, although 63% of United States cancer patients were over 65 years old, the elderly comprised only 25% of trial participants.¹⁸ However, this study evaluated elderly participation using data from only one cooperative group. Furthermore, the investigators did not evaluate whether elderly participation differed by phase of the trial or stage of disease, or investigate the reasons for the underrepresentation among the elderly. Recent federal efforts have focused on expanded Medicare coverage for clinical trials. To assess the likely impact of improved insurance coverage, it is important to determine the numerous factors that may affect the representation of elderly persons in cancer clinical trials.

This article evaluates the participation of the elderly in NCI-sponsored cancer treatment trials active from 1997 through 2000 using data from multiple cooperative groups. We examine the participation of elderly patients in clinical trials stratified by trial phase (II v III) and by stage of disease (early v late). Most important, we assess the impact of clinical trial protocol exclusions on elderly participation in trials.

	PATIENTS AND METHODS

TOP ABSTRACT INTRODUCTION PATIENTS AND METHODS RESULTS DISCUSSION APPENDIX 1. APPENDIX 2. APPENDIX 3: REFERENCES

 
Data Sources
We used three NCI databases: the Cancer Therapy Evaluation Program (CTEP),¹⁹ the Physician Data Query (PDQ),²⁰ and the Surveillance, Epidemiology, and End Results Program (SEER).²¹ The CTEP and the PDQ were used to detail the characteristics of NCI-sponsored clinical trials, including the age distribution of trial participants. The SEER data were used to compute national cancer incidence rates for the elderly, so that the proportion of patients enrolled onto clinical trials who were elderly could be compared with the corresponding proportion of the population with cancer.

The CTEP Database
CTEP is responsible for planning, assessing, and coordinating clinical trials. As the manager of the collaborative clinical trial groups, the CTEP is a data clearinghouse to which investigators report their progress with each protocol. The CTEP data include protocol identification numbers, trial phase, planned and actual trial accrual, date when the trial began to enroll patients, end date, and participation by age. Our study focused on 495 adult, phase II and III cancer treatment trials that were conducted by cooperative groups and enrolled patients between 1997 and 2000. We chose to evaluate only cooperative group trials because of the strict reporting requirements for the groups; the CTEP database is considered complete for cooperative group trials active in 1997 and beyond.

The PDQ Database
The PDQ database contains detailed protocol exclusion criteria for NCI-sponsored clinical trials. For each of the 495 trials in the study, we determined the cancer type and stage, planned trial duration, and protocol exclusion criteria. Appendix 1 details the specific exclusions that we defined for each category of protocol exclusion criteria. Strict exclusions were those protocol exclusion criteria that required normal or nearly normal laboratory values or organ system function, whereas moderate exclusions allowed for mildly abnormal values while still imposing restrictions.

To define functional status exclusions, we created a new performance score by matching the Karnofsky scores with the Eastern Cooperative Oncology Group (ECOG)/Zubrod scores.^22,23 The majority of the protocols used the ECOG/Zubrod score, which assigns patients a score from 0 to 5 on the basis of their ability to carry on activities of daily living. A number of trials used the Karnofsky score, which rates functional status from 0% to 100% of normal health. Appendix 1 also provides a table relating our exclusion definitions to the ECOG/Zubrod and Karnofsky scales. We defined three levels of functional status restrictions. Each trial was coded to reflect the protocol requirement that participants be able to function at the specified level or better. Thus, a trial with the most restrictive functional status requirements would require participants to be ambulatory and able to work, whereas a trial with the most lenient functional status requirement would allow patients to enroll who were nonambulatory and had limited self-care capabilities.

Life expectancy requirements, where present, ranged from 1 month to 10 years. We categorized life expectancy criteria into the following two groups: protocols with life expectancy requirements of 6 months and those with requirements greater than 6 months. Age restrictions for minimum or maximum age were recorded. If a trial specified that enrollees must be postmenopausal, the minimum age restriction was recorded as 50 years. Other exclusions included the requirements that patients have no history of psychiatric problems specific to the elderly, such as organic brain syndrome, Alzheimer’s disease, or senility; have no history of other neurologic or psychiatric disorders, other cancers, human immunodeficiency virus or AIDS, other severe disease, or active infections; and not be pregnant.

We stratified cancer trials by the stage of the cancer being treated to determine whether the elderly were more or less likely to be represented in trials for the treatment of early-stage or late-stage cancers. Appendix 2 details the stage categories used for each cancer type. In general, stage I and II cancers were considered early-stage cancers and stage III and IV cancers were considered late-stage cancers. Some protocols treated patients with varying stages of cancer that crossed over this division and, therefore, could not be classified.

The SEER Database
The SEER Program of the NCI is the most authoritative source of information on cancer incidence and survival in the United States.²¹ The SEER data are gathered from 11 tumor registries covering approximately 13.6% of the United States general population and 12.3% of the United States population age 65 years or older.^24,25 The SEER program includes population-based information regarding cancer patient demographics, primary tumor type, morphology, stage at diagnosis, first course of treatment, and follow-up vital status.

To calculate the proportion of the United States population with each cancer type who were 65 years or older, we adjusted the incidence rates from the 1997 SEER data to reflect the proportion of elderly in the nation as a whole. We used 1998 data from the United States Census Bureau to determine the number of elderly and the total population in all of the counties represented in the 11 SEER registries. We then aggregated the number of new cases of cancer among the elderly and the total population by cancer type. We divided the aggregate numbers by the respective populations in the SEER areas to yield the SEER incidence rates for each cancer in both the elderly and the total population. Next, incidence rates for the elderly and the total population within SEER registry counties for each type of cancer were multiplied by the number of elderly and the total population within the United States to yield the number of new cases nationally for both groups. We then divided the national number of new cases of cancer among the elderly by the national number of new cases of cancer in the total population to calculate the estimated proportion of the total population diagnosed with cancer who were elderly. Proportions were calculated for 18 specific cancer types, for all cancer types combined, and for early- and late-stage cancers.

Statistical Analysis
We evaluated the distribution of elderly participants across trials and for trials stratified by cancer type, phase, and stage. We compared the participation rates with the proportions of the elderly in the United States population with each cancer type using one-sample binomial tests. Two tailed P values of .05 or less were considered to indicate statistical significance.²⁶

We used a weighted linear regression to examine the association between the proportion of elderly participants in each trial, as the dependent variable, and the year the trial opened, trial phase, and protocol exclusion criteria.²⁷ We forced indicator variables for cancer type and cancer stage, and their interactions, into the model to control for epidemiologic differences in age distribution across cancer types. Variables for the year the trial opened, trial phase, and protocol exclusion criteria were chosen for inclusion using a backward stepwise selection procedure set to retain only variables that were significant at the P = .05 level. Each trial was weighted by its total enrollment in the linear regression model.

The regression results were subjected to several regression diagnostics, including residual analysis and an examination of outliers. Furthermore, the regression findings were robust to alternative model specifications, including specifying the dependent variable as a logistic transformation of the proportion of participants in each trial who were elderly. We present the results on the basis of the model with the untransformed dependent variable for ease of interpretation.

Predictions
We used the regression results to predict the proportion of elderly in each cancer trial that would have been expected in the absence of protocol exclusion criteria. We used two prediction models. We first relaxed the protocol exclusions that were based on organ system abnormalities by setting the values of the indicator variables for these exclusions to 0 for all trials and using the parameter estimates to predict the proportion of elderly in each trial. In the second model, we relaxed both exclusions that were based on organ-system abnormalities and exclusions that were based on functional status limitations.

	RESULTS

TOP ABSTRACT INTRODUCTION PATIENTS AND METHODS RESULTS DISCUSSION APPENDIX 1. APPENDIX 2. APPENDIX 3: REFERENCES

 
Descriptive Data
Overall, 32% of the participants in the clinical trials were elderly, compared with 61% of patients with incident cancers in the United States population who are age 65 years or older. Figure 1 shows the proportions of elderly patients in phase II and III trials for 18 cancer types compared with the proportions of the United States population with each cancer type who are elderly. The elderly were significantly underrepresented (P < .05) in phase III melanoma trials; phase II CNS, gastroesophageal, renal, and soft tissue cancer trials; and phase II and III breast, cervical, colorectal, head and neck, leukemia, lung, and uterine cancer trials.

View larger version (36K): [in this window] [in a new window]   Fig 1. Comparison of elderly participation in phase II and III trials with percent of United States cancer patients who are elderly.

Predictions
When we relaxed the cardiac function, hypertension, hematologic, and pulmonary function exclusions, the overall predicted proportion of elderly patients increased to 46.7%. When we relaxed both the organ system and functional status exclusions, the overall predicted proportion of elderly patients increased to 59.7% (Fig 2).

View larger version (12K): [in this window] [in a new window]   Fig 2. Predicted elderly enrollment when exclusion criteria are relaxed. Exclusions include cardiac function, hypertension, hematologic, and pulmonary function.

	DISCUSSION

TOP ABSTRACT INTRODUCTION PATIENTS AND METHODS RESULTS DISCUSSION APPENDIX 1. APPENDIX 2. APPENDIX 3: REFERENCES

Although the elderly were underrepresented in the trials we evaluated, they comprised a larger proportion of clinical trial participants than previously reported. Expanding the analysis to all cooperative groups and focusing on the last 4 years narrowed the gap between the 61% of the cancer population who are elderly and the previously reported 25% of cancer clinical trial participants who are elderly.¹⁸ Using the more comprehensive data, we found that 32% of patients in cancer trials were age 65 years or older.

We did not find a significant difference in elderly participation between phase II and phase III clinical trials. Phase II clinical trials are generally smaller, nonrandomized studies that evaluate both the toxicity and anticancer effects of therapies. Phase III trials build on the knowledge from the phase II trials and are generally randomized controlled trials comparing a new treatment or an investigational protocol to the standard of care.

This study is the first comprehensive study to summarize the protocol exclusion criteria that are used in cancer clinical trials and relate them to elderly participation.²⁸ Older patients are more likely to have medical histories and conditions that make them ineligible for cancer treatment trials that include protocol exclusions. Our prediction models demonstrate the substantial impact of restrictive protocol exclusion criteria on elderly participation.

Of course, protocol exclusion criteria are not arbitrary. For example, it is important that participants in trials that use nephrotoxic chemotherapies have normal renal function. Similarly, pulmonary and cardiac toxicity can be risks of cancer treatment, and it is reasonable for certain trials to require ample pulmonary or cardiac reserve for the patients to tolerate the therapy. Comorbidity also can affect survival, and elderly patients with comorbid conditions may be more likely to die of causes other than the cancer being treated, making treatment effects more difficult to detect.^3,29 Nonetheless, protocol exclusion criteria that are based on comorbid conditions or functional status limitations disproportionately disqualify older patients from clinical trials. When designing a clinical trial, investigators must examine each protocol exclusion and be certain that it is scientifically justified for a particular trial before including it in the protocol.

As the United States population ages a greater proportion of cancer patients will be elderly. Studies of many different cancers have demonstrated age-related differences in the natural history of cancer and in the effect of cancer treatment. For example, in prostate cancer, age has been found to be an independent predictor of distant metastases after treatment.³⁰ In non-Hodgkin’s lymphoma, age greater than 65 years has been found to be a significant negative prognostic factor.³¹ Studies of leukemias have found that older patients do not tolerate intensive treatment as well as younger patients.^32,33 In addition, specific biologic characteristics in older patients can be associated with poor outcomes,³⁴ and there is evidence that hematologic, cardiac, gastrointestinal, and neurologic toxicity related to chemotherapy may be more severe in older patients.³⁵ Therefore, to ensure that cancer trials develop and evaluate therapies for all patients with cancer, trials will need to enroll elderly patients in sufficient numbers.

It is legitimate to question whether cancer trials should recruit older subjects in proportion to their cancer incidence. Achieving such a goal would involve major redesign of investigative protocols and considerable expense. Furthermore, if the elderly with comorbidities are less likely than younger adults to benefit from certain therapies, increasing elderly participation in clinical trials could produce less-conclusive results with smaller treatment effects.

Even though proportionate participation of the elderly in trials may not be desirable or feasible, it is important to determine the factors that influence elderly participation in trials and to ensure that the elderly have access to trials. It may be necessary to design more trials that focus exclusively on elderly subjects or that address the treatment of cancer patients with specific comorbidities. Similarly, it may be important that certain cancer trials enroll elderly patients in sufficient numbers to allow for statistically meaningful subgroup analyses. More information is needed on the differential response to and tolerance of chemotherapies by age and in individuals with and without comorbidities.

Our study has several limitations. First, we did not have the data to determine the degree to which the protocol exclusions were followed. However, all of the trials in our sample were audited according to the CTEP guidelines.

Second, our regression analyses do not demonstrate that protocol exclusion criteria are causally related to lower elderly participation; rather, they reveal associations that in some cases may have alternative explanations. Our finding of an association between life expectancy requirements and higher elderly participation was unexpected. These trials may have been actively targeting older populations, and therefore, the investigators may have felt it important to specify life expectancy exclusions. Despite this unexpected finding, it seems likely that most of the associations that we found between elderly participation and protocol exclusions on the basis of organ-system abnormalities or functional status limitations represent causal relationships.

Finally, our study did not assess the nonclinical factors that may influence elderly participation in cancer trials. For example, older patients may be less likely to seek out clinical trials¹⁶ and may be more inclined than younger patients to obtain treatment from their community physicians rather than transfer their care to academic medical centers or cancer centers. Differences in elderly persons’ preferences for trials could be a result of differences in education, stronger relationships with primary care physicians, or difficulty getting to and from distant providers. The frequent visits required for aggressive cancer care or to participate in clinical trials may not be feasible for elderly persons who live alone or lack social supports. In addition, the elderly and their families may have preconceived notions about the potential benefits to elderly patients from participating in clinical trials or from aggressive cancer therapy.

Previous research indicates that investigators may be reluctant to enroll elderly patients in clinical trials.³⁶ This may be because of preconceived notions about the ability of the elderly to tolerate aggressive therapy. For example, the elderly have been found to be less likely to receive aggressive cancer treatment despite a lack of evidence that age is a risk factor for drug toxicity or surgical mortality.³⁷ Elderly breast cancer patients receive less aggressive care, independent of the presence of comorbidities.³⁸

The NCI has several initiatives in place to assess the impact of various factors that may affect the recruitment of older patients to clinical trials and to determine the effect of comorbidities on tolerance of cancer treatment.^16,39 Future research should examine the preferences of the elderly regarding participation in trials, as well as the beliefs and behaviors of investigators regarding participation of the elderly in trials.

The results of our study indicate that recent federal policy to expand Medicare coverage for cancer clinical trials, by itself, is unlikely to substantially increase the level of elderly participation in cancer treatment trials. We found that protocol exclusions that are based on organ-system abnormalities and functional status limitations in NCI-sponsored trials disproportionately disqualify the elderly from participation and almost fully account for elderly patients’ underrepresentation in trials relative to their cancer burden. Without a better understanding of the scientific justification for these exclusions, more trials focused on the elderly, or changes in study design or requirements, many cancer clinical trials may fail to provide the best possible evidence for treating elderly patients with cancer.

	APPENDIX 1.

TOP ABSTRACT INTRODUCTION PATIENTS AND METHODS RESULTS DISCUSSION APPENDIX 1. APPENDIX 2. APPENDIX 3: REFERENCES

 

Protocol Entry Criteria Exclusions for Comorbid Conditions

Moderate Restrictions Strict Restrictions Hematology     Adequate hematologic function Normal or near normal required     WBC 3,000/mm3 WBC 4,000     WBC 3,500/mm3 ANC 1,800     ANC 1,000/mm3 ANC 2,000     ANC 1,200/mm3 Granulocyte 1,800     ANC 1,500/mm3 Granulocyte 2,000     Granulocyte 1,000/mm3 PLT normal     Granulocyte 1,500/mm3 PLT 130,000     PLT 75,000/mm3 HgB or Hct normal     PLT 100,000/mm3     PLT 125,000/mm3     Hg 8 g/dL     Hg 9 g/dL     Hg 10 g/dL     Hg 11 g/dL or Hct 33%     Bone marrow cellularity 30%     Fibrinogen 200 mg/dL Hepatic     Adequate hepatic function LFTs normal or near normal     No acute hepatitis Bilirubin normal     Hepatitis C status required Bilirubin < 1.2 x NL     LFT 2 x NL to < 5 x NL Bilirubin 1.5 x NL     LFT 2.5 x NL Bilirubin 1.5 mg/dL     Bilirubin < 2 x NL mg/dL DBIL normal     Bilirubin 2.5 x NL mg/dL AST/ALT normal     Bilirubin 2 mg/dL AST/ALT < 1.2 NL     Bilirubin 5 mg/dL AST/ALT < 1.5 NL     DBIL < 0.3 mg above NL mg/dL AST 60 IU/mL     AST/ALT < 2 NL U/L AST 40 IU/mL     AST/ALT < 2.5 NL U/L ALT 56 IU/mL     AST/ALT < 3 NL U/L GGT NL     AST/ALT < 4 NL U/L AP NL     AST/ALT < 5 NL U/L AP < 1.2 x NL     GGT < 2 x NL U/L LDH NL     GGT < 3 x NL U/L     AP < 2 x NL U/L     AP < 3 x NL U/L     AP < 4 x NL U/L     AP < 5 x NL U/L     LDH < 2 x NL     LDH < 2 x NL     LDH < 3 x NL     Triglycerides 320 mg/dL     PT NL     PTT NL     Thrombin time NL Renal     Adequate renal function Normal renal function     Creatinine clearance 50 mL/min Creatinine clearance 70     Creatinine clearance 60 mL/min Creatinine normal     Creatinine < 2 mg/dL Creatinine < 1.2 mg/dL     Creatinine < 0.8 mg above NL Creatinine < 1.5 mg/dL Congestive heart failure (CHF); cardiac function     No condition adversely affected by sinus bradycardia No history CHF     Adequate cardiac function No cardiomegaly on CXR or LVH on ECG unless LVEF 45%     No uncontrolled or severe cardiovascular disease Normal MUGA or echo     No active cardiac disease that precludes doxorubicin or docetaxel NL LVEF     No clinically evident CHF LVEF 45%     No difficult to control CHF LVEF 45% and 50% with ex, or LVEF 55%     NYHA class II required (if protocol states I or II then put here; = no class III or IV) LVEF 50% on MUGA     No valvular disease with cardiac function compromise NYHA class I required (= no NYHA class II/III/IV)     No pericarditis or myocarditis     No cardiomyopathy Coronary artery disease     No MI past 12 months No active angina     No MI past 6 months No MI ever     No MI past 3 months No MI past 5 years     No MI past 6 weeks No history of ischemic heart disease     No CABG past 6 months     No unstable angina     No angina requiring medication Cardiac electrophysiology problems     No unstable heart rhythm No abnormal conduction disease     No major ventricular arrhythmia No arrhythmia requiring treatment     No arrhythmia associated with heart failure     No arrhythmia that is difficult to control     No cardiac medications that alter cardiac conduction     No symptomatic arrhythmia within past 6 months     Conduction disease allowed if stable for 6 months Hypertension     No poorly controlled hypertension No history of hypertension     No systolic BP > 200 mmHg or diastolic BP > 120 mmHg No diastolic BP > 100 mmHg No systolic BP > 160 mmHg or diastolic BP > 100 mmHg Other cardiovascular     No thromboembolic disease past 6 months No history of peripheral vascular disease     No History DVT past 6 months No history of stroke No history of TIA No thromboembolic disease history No history of chronic CVA No history of DVT No history of PE

Protocol Exclusion Criteria: Performance Status Score Relating the ECOG/Zubrod and the Karnofsky Scores Summary Exclusion Rating ECOG/Zubrod Score Karnofsky Score 0 = Fully active, able to carry on all predisease performance without restriction 100 = Normal, no complaints; no evidence of disease 90 = Able to carry on normal activity, minor signs or symptoms of disease 1 1 = Restricted in physically strenuous activity but ambulatory and able to carry out work of a light or sedentary nature, eg, light house work, office work  80 = Normal activity with effort, some signs or symptoms of disease 70 = Cares for self but unable to carry on normal activity or to do active work 2 2 = Ambulatory and capable of all self-care but unable to carry out any work activities up and about more than 50% of waking hours  60 = Requires occasional assistance but is able to care for most of personal needs 50 = Requires considerable assistance and frequent medical care 3 3 = Capable of only limited self-care, confined to bed or chair more than 50% of waking hours  40 = Disabled; requires special care and assistance 30 = Severely disabled; hospitalization is indicated, although death not imminent 4 = Completely disabled; cannot carry on any self-care; totally confined to bed or chair  20 = Very ill; hospitalization and active supportive care necessary 10 = Moribund 5 = Deceased  0 = Deceased NOTE. Pulmonary and psychiatric exclusion criteria are available on request from the author. Abbreviations: ANC, absolute neutrophil count; PLT, platelets; Hct, hematocrit; Hg, hemoglobin; AST, aspartate aminotransferase; ALT, alanine aminotransferase; LFT, liver function test; NL, normal limit; DBIL, direct bilirubin; GGT, gamma-glutamyl transpeptidase; AP, alkaline phosphatase; LDH, lactate dehydrogenase; PT, prothrombin time; PTT, partial thromboplastin time; NYHA, New York Heart Association; MI, myocardial infarction; CABG, coronary artery bypass grafting; BP, blood pressure; DVT, deep venous thrombosis; CXR, chest x-ray; LVH, left ventricular hypertrophy; LVEF, left ventricular ejection fraction; MUGA, multigated acquisition; TIA, transient ischemic attack; CVA, cerebrovascular accident; PE, pulmonary embolism; ECOG, Eastern Cooperative Oncology Group.

	APPENDIX 2.

TOP ABSTRACT INTRODUCTION PATIENTS AND METHODS RESULTS DISCUSSION APPENDIX 1. APPENDIX 2. APPENDIX 3: REFERENCES

 

Categories for Early- and Late-Stage Cancers, Coding for Trials and for Population Using SEER Staging¹⁹

Bladder     Early: stage I, II, localized, carcinoma-in-situ, stage Ta transitional     Late: stage III, IV, refractory, relapsed, or metastatic Breast     Early: stage 0, I, II, trials that treat people who are in either stage II or IIIa, in-situ, localized, or regional by direct extension     Late: stage III, IV, advanced or metastatic Cervical     Early: stage 0, I, II, in situ, or localized     Late: stage III, IV, incurable, advanced, or inoperable CNS     Early: localized, regional by direct extension     Late: distant, unresectable, aggressive, poor-risk, recurrent, or advanced Colorectal     Early: stage 0, I, II, in situ, localized, or completely resected     Late: stage III, IV, distant, metastatic, or advanced Gastroesophageal     Early: in situ, localized, regional by direct extension, or resectable     Late: regional by nodes, distant, advanced, unresectable, or metastatic Head and neck     Early: stage I, II, in situ, localized, resectable, or regional by direct extension     Late: stage III, IV, regional by nodes, distant, advanced, or metastatic Lung     Early: stage 0, I, II, in situ, localized, or limited stage     Late: stage III, IV, advanced, metastatic, or extensive stage Lymphoma: Hodgkin’s and non-Hodgkin’s     Early: stage 0, I, II, or localized     Advanced: stage III, IV, advanced, or distant Melanoma     Early: stage 0, I, II, in situ, localized, regional by direct extension     Late: stage III, IV, regional by nodes, distant, advanced, or metastatic Ovarian     Early: stage 0, I, II, in situ, localized, or regional by direct extension     Late: stage III, IV, regional by nodes, distant, or metastatic Pancreatic     Early: stage I, II, in situ, localized, or regional by direct extension     Late: stage III, IV, regional by nodes, distant, or metastatic Prostate     Early: stage 0, I, II, or in situ     Late: stage III, IV, distant, or metastatic Renal     Early: in situ, localized, or regional by direct extension     Late: regional by nodes, distant, advanced, or metastatic Soft tissue sarcoma     Early: stage I, II, localized, or regional by direct extension     Late: stage III, IV, regional by nodes, distant, or advanced Uterine     Early: stage I, II, or localized     Late: stage III, IV, regional by nodes, distant, or metastatic

	APPENDIX 3:

TOP ABSTRACT INTRODUCTION PATIENTS AND METHODS RESULTS DISCUSSION APPENDIX 1. APPENDIX 2. APPENDIX 3: REFERENCES

 

Regression Results

Coefficient ± SE t P > t 95% CI Protocol exclusion criteria     Parameter         No hypertension -0.053 ± 0.022 -2.340 .020 -0.097 to -0.008         No abnormal cardiac function -0.086 ± 0.017 -5.000 .000 -0.120 to -0.052         No hematologic function abnormality -0.141 ± 0.019 -7.530 .000 -0.177 to -0.104         No impaired pulmonary function -0.093 ± 0.025 -3.780 .000 -0.141 to -0.044         Any specified life expectancy 0.035 ± 0.015 2.360 .019 0.006 to 0.065     Functional status*         No mild functional status impairment -0.223 ± 0.035 -6.390 .000 -0.292 to -0.155         No moderate functional status impairment -0.226 ± 0.034 -6.660 .000 -0.293 to -0.159         No functional status criteria specified -0.289 ± 0.033 -8.700 .000 -0.355 to -0.224 Disease characteristics     Late-stage disease 0.239 ± 0.048 5.020 .000 0.145 to 0.332     Cancer site         Bladder 0.246 ± 0.100 2.460 .014 0.049 to 0.443         Breast 0.098 ± 0.056 1.760 .080 -0.012 to 0.207         CNS 0.046 ± 0.076 0.610 .539 -0.102 to 0.195         Cervical -0.132 ± 0.100 -1.320 .188 -0.328 to 0.064         Colorectal 0.316 ± 0.059 5.340 .000 0.200 to 0.432         Gastroesophageal 0.278 ± 0.093 3.010 .003 0.096 to 0.460         Head and neck 0.221 ± 0.261 0.850 .397 -0.292 to 0.734         Leukemia -0.090 ± 0.078 -1.150 .252 -0.244 to 0.064         Lung 0.313 ± 0.065 4.780 .000 0.184 to 0.441         Lymphoma 0.197 ± 0.077 2.580 .010 0.047 to 0.348         Melanoma 0.097 ± 0.076 1.280 .203 -0.052 to 0.246         Myeloma 0.500 ± 0.157 3.180 .002 0.191 to 0.810         Ovarian -0.129 ± 0.089 -1.450 .148 -0.303 to 0.046         Pancreatic 0.267 ± 0.098 2.730 .007 0.075 to 0.460         Prostate 0.342 ± 0.096 3.550 .000 0.152 to 0.531         Renal -0.063 ± 0.127 -0.490 .621 -0.312 to 0.186         Soft tissue sarcoma -0.100 ± 0.106 -0.950 .345 -0.308 to 0.108         Uterine 0.034 ± 0.053 0.650 .518 -0.069 to 0.137     Site x stage interactions         Late-stage breast -0.215 ± 0.068 -3.170 .002 -0.348 to -0.081         Late-stage CNS -0.167 ± 0.078 -2.130 .034 -0.321 to -0.013         Late-stage cervical -0.190 ± 0.106 -1.790 .074 -0.399 to 0.019         Late-stage colorectal -0.193 ± 0.063 -3.040 .002 -0.317 to -0.068         Late-stage gastroesophageal -0.222 ± 0.120 -1.850 .065 -0.458 to 0.014         Late-stage head and neck -0.329 ± 0.262 -1.260 .210 -0.843 to 0.185         Late-stage leukemia 0.085 ± 0.084 1.000 .316 -0.081 to 0.251         Late-stage lung -0.209 ± 0.063 -3.320 .001 -0.332 to -0.085         Late-stage lymphoma -0.216 ± 0.086 -2.510 .013 -0.386 to -0.047         Late-stage melanoma -0.222 ± 0.089 2.480 .013 -0.398 to -0.046     Late-stage myeloma -0.535 ± 0.162 -3.300 .001 -0.853 to -0.217         Late-stage ovarian 0.051 ± 0.089 0.570 .568 -0.124 to 0.227         Late-stage pancreatic -0.225 ± 0.107 -2.090 .037 -0.436 to -0.014         Late-stage prostate -0.087 ± 0.093 -0.930 .350 -0.271 to 0.096         Intercept 0.523 ± 0.059 8.870 .000 0.407 to 0.639 NOTE. The dependent variable is the proportion of trial enrollees who were aged 65 years or older (N = 495); the adjusted R2 statistic was 0.653. Abbreviation: CI, confidence interval. *Omitted variable is no severe functional status impairment.

	ACKNOWLEDGMENTS

 
We thank Mary McCabe for her counsel. We also thank Nikhil Wagle for his assistance with data abstraction and Kris Parker for her assistance in preparing the article.

	NOTES

 
Supported in part by the National Cancer Institute, with additional funding from the Office of the Director, National Institutes of Health, and the National Science Foundation. This research was also sponsored in part by the Robert Wood Johnson Clinical Scholars Program and by the Veterans Affairs (VA) Ambulatory Care Fellowship in Health Services Research at the West Los Angeles VA Medical Center (J.H.L.).

The opinions expressed in this article are solely those of the authors.

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