Cary P. Gross

Predicting Chemotherapy Toxicity in Older Adults With Cancer: A Prospective Multicenter Study

PURPOSE Older adults are vulnerable to chemotherapy toxicity; however, there are limited data to identify those at risk. The goals of this study are to identify risk factors for chemotherapy toxicity in older adults and develop a risk stratification schema for chemotherapy toxicity. PATIENTS AND METHODS Patients age ≥ 65 years with cancer from seven institutions completed a prechemotherapy assessment that captured sociodemographics, tumor/treatment variables, laboratory test results, and geriatric assessment variables (function, comorbidity, cognition, psychological state, social activity/support, and nutritional status). Patients were followed through the chemotherapy course to capture grade 3 (severe), grade 4 (life-threatening or disabling), and grade 5 (death) as defined by the National Cancer Institute Common Terminology Criteria for Adverse Events. RESULTS In total, 500 patients with a mean age of 73 years (range, 65 to 91 years) with stage I to IV lung (29%), GI (27%), gynecologic (17%), breast (11%), genitourinary (10%), or other (6%) cancer joined this prospective study. Grade 3 to 5 toxicity occurred in 53% of the patients (39% grade 3, 12% grade 4, 2% grade 5). A predictive model for grade 3 to 5 toxicity was developed that consisted of geriatric assessment variables, laboratory test values, and patient, tumor, and treatment characteristics. A scoring system in which the median risk score was 7 (range, 0 to 19) and risk stratification schema (risk score: percent incidence of grade 3 to 5 toxicity) identified older adults at low (0 to 5 points; 30%), intermediate (6 to 9 points; 52%), or high risk (10 to 19 points; 83%) of chemotherapy toxicity (P < .001). CONCLUSION A risk stratification schema can establish the risk of chemotherapy toxicity in older adults. Geriatric assessment variables independently predicted the risk of toxicity.

The Relation between Funding by the National Institutes of Health and the Burden of Disease

BACKGROUND The Institute of Medicine has proposed that the amount of disease-specific research funding provided by the National Institutes of Health (NIH) be systematically and consistently compared with the burden of disease for society. METHODS We performed a cross-sectional study comparing estimates of disease-specific funding in 1996 with data on six measures of the burden of disease. The measures were total mortality, years of life lost, and number of hospital days in 1994 and incidence, prevalence, and disability-adjusted life-years (one disability-adjusted life-year is defined as the loss of one year of healthy life to disease) in 1990. With the use of these measures as explanatory variables in a regression analysis, predicted funding was calculated and compared with actual funding. RESULTS There was no relation between the amount of NIH funding and the incidence, prevalence, or number of hospital days attributed to each condition or disease (P=0.82, P=0.23, and P=0.21, respectively). The numbers of deaths (r=0.40, P=0.03) and years of life lost (r=0.42, P=0.02) were weakly associated with funding, whereas the number of disability-adjusted life-years was strongly predictive of funding (r=0.62, P<0.001). When the latter three measures were used to predict expected funding, the conclusions about the appropriateness of funding for some diseases varied according to the measure used. However, the acquired immunodeficiency syndrome, breast cancer, diabetes mellitus, and dementia all received relatively generous funding, regardless of which measure was used as the basis for calculating support. Research on chronic obstructive pulmonary disease, perinatal conditions, and peptic ulcer was relatively underfunded. CONCLUSIONS The amount of NIH funding for research on a disease is associated with the burden of the disease; however, different measures of the burden of disease may yield different conclusions about the appropriateness of disease-specific funding levels.

Recruiting Vulnerable Populations into Research: A Systematic Review of Recruitment Interventions

BackgroundMembers of vulnerable populations are underrepresented in research studies.ObjectiveTo evaluate and synthesize the evidence regarding interventions to enhance enrollment of vulnerable populations into health research studies. Data sourcesStudies were identified by searching MEDLINE, the Web of Science database, personal sources, hand searching of related journals, and article references. Studies that contained data on recruitment interventions for vulnerable populations (minority, underserved, poor, rural, urban, or inner city) and for which the parent study (study for which recruitment was taking place) was an intervention study were included. A total of 2,648 study titles were screened and 48 articles met inclusion criteria, representing 56 parent studies. Two investigators extracted data from each study.ResultsAfrican Americans were the most frequently targeted population (82% of the studies), while 46% targeted Hispanics/Latinos. Many studies assessed 2 or more interventions, including social marketing (82% of studies), community outreach (80%), health system recruitment (52%), and referrals (28%). The methodologic rigor varied substantially. Only 40 studies (71%) incorporated a control group and 21% used statistical analysis to compare interventions. Social marketing, health system, and referral recruitment were each found to be the most successful intervention about 35–45% of the studies in which they were attempted, while community outreach was the most successful intervention in only 2 of 16 studies (13%) in which it was employed. People contacted as a result of social marketing were no less likely to enroll than people contacted through other mechanisms.ConclusionsFurther work with greater methodologic rigor is needed to identify evidence-based strategies for increasing minority enrollment in research studies; community outreach, as an isolated strategy, may be less successful than other strategies.

Racial disparities in cancer therapy: Did the gap narrow between 1992 and 2002?

The purpose of this study was to determine whether racial disparities in cancer therapy had diminished since the time they were initially documented in the early 1990s.

Reporting the Recruitment Process in Clinical Trials: Who Are These Patients and How Did They Get There?

Context The value of randomized, controlled trials often depends on generalizability of the findings. However, persons recruited for these studies may not be representative of the population of interest. Contribution Randomized, controlled trials recently published in four high-impact medical journals were reviewed to evaluate the recruitment process. Only half of the trials reported the number of persons who were evaluated for eligibility, and 43% reported how many were actually eligible. The proportion of screened potential participants who were eligible and actually enrolled varied widely. Implications Because the patient recruitment process is often poorly delineated, it is difficult to judge the generalizability of findings reported in many randomized, controlled trials. The Editors Randomized, controlled trials (RCTs) are frequently hailed as the gold standard of study designs for determining the efficacy of different interventions (1). The adequacy of reporting in RCTs has received increased attention during the past decade, because some reviews have suggested that investigators often do not report enough methodologic information to allow readers to effectively assess their studies (2-5). Meetings held by journal editors and investigators in the mid-1990s culminated in the publication of the Consolidated Standards of Reporting Trials (CONSORT) statement in 1996 (6). These guidelines primarily focused on information relevant to the internal validity of trials. They required detailed information about entry criteria, method of randomization, patient follow-up, outcome assessment, and analytic plan (6-8). The CONSORT initiative has been criticized for underemphasizing the issue of external validity by failing to require authors to report information about the source population, when feasible (9). Before using the results of an RCT for treating an individual patient, a clinician must determine whether his or her patient differs from those who participated in the trial in a meaningful way. Therefore, it is important to evaluate how the RCT sample was assembled from the general population (10). This trial recruitment process can be described with qualitative and quantitative data, both of which can contribute important information about the generalizability of the RCT. After selecting a condition of interest, investigators must decide which people are potentially eligible to participate, that is, the target population. The definition of the target population can have a significant impact on the generalizability of the study. For example, when recruiting people for a study of hypertension, investigators could target patients in hypertension clinics, the patients of primary care physicians, or previously undiagnosed persons who were identified as being hypertensive at community screenings. After defining the target population, the investigators must engage a subgroup of this population by identifying and approaching these potential participants (Figure). Figure. The trial enrollment process. The next steps in the recruitment process, which can be described with readily available quantitative data, can also have a significant impact on generalizability (Figure). If only a small proportion of potential participants eventually enroll in a study, the concern arises that participants differ from nonparticipants as a result of eligibility criteria or other factors. Potential participants undergo eligibility screening to determine who is eligible for participation (this proportion is termed the eligibility fraction) (Table 1). Persons who are eligible for participation (Figure) are then asked to provide informed consent and enroll in the study (this proportion is termed the enrollment fraction). The product of these two fractions represents the proportion of potential participants who actually enrolled in the study (termed the recruitment fraction) (Table 1). Table 1. Trial Recruitment Terminology Using a standardized abstraction instrument, we assessed whether the quantitative enrollment experience was being reported clearly in RCTs published in four high-impact medical journals. We also analyzed the available data to estimate whether trial enrollees represented a highly selected population and to gain insight into the methods for reporting the recruitment process. Methods Sources of Data Using four journals and selecting only investigations involving interventions in humans, we reviewed all RCTs published in a 1-year period starting 1 April 1999. We conducted a manual search of all articles published under the following headings: articles (Annals of Internal Medicine), original contributions (The Journal of the American Medical Association), original research (The Lancet), and original articles (The New England Journal of Medicine). Because we wanted to study the enrollment process on an individual basis, only RCTs that involved individual people as the unit of randomization (rather than a hospital or region, for example) were included. Subgroup or follow-up analyses of a previously published study, reports of the results of multiple RCTs in a single article, and investigations of diagnostic strategies (rather than therapeutic interventions) were also excluded. Data Collection Articles were screened, selected, and abstracted by two independent investigators using a standardized abstraction instrument. Results were compared by a third party, and disagreements were resolved by consensus. We recorded the following information: journal, sources of support, type of intervention, clinical area, and number of people who were screened (to determine whether they were eligible). We used a strict definition of the number of people screened in our quantitative analysis of the eligibility and recruitment fractions. Only RCTs that reported the number of potential participants in a specific target population were included in this portion of the analysis. For example, in a trial of antihypertensive therapy, investigators evaluated 10 000 adults in the general population and identified 1000 with hypertension who were then evaluated for trial eligibility. We used 1000 as the number of patients screened. We also abstracted information on the number of patients who were eligible, the number who were eligible but declined enrollment, the number who actually enrolled, and the mortality rate in the control group. Information about eligible nonparticipants was also recorded, when available. The type of intervention for each trial was categorized as pharmaceutical therapy, behavioral therapy, surgery, nonsurgical procedures, and other. Studies were also categorized by source of support: pharmaceutical industry, government, foundation, and other. The eligibility and enrollment fractions were defined, and the recruitment fraction was defined as the product of these fractions (Table 1 and Figure): the proportion of potential participants who were approached by the investigators and who subsequently enrolled. The number needed to screen to identify one person who would actually enroll in a trial was calculated by dividing 1 by the recruitment fraction. Finally, to develop a proxy for disease severity, we grouped the RCTs according to the mortality rate in their control groups. Statistical Analysis Results were summarized and reported as proportions; a chi-square test was used to evaluate differences among groups. We used an adaptation of the Wilcoxon rank-sum test as a nonparametric test for trend across ordered groups to determine whether there was an association between recruitment fraction and mortality rate in the control group (11). We used Spearman rank correlation coefficients as well as t-tests to determine whether the number needed to screen for each patient enrolled was related to study size, source of funding, or type of control intervention. We also used an analysis of variance (ANOVA) model for multiple group comparison tests to identify differences in the number needed to screen among groups. Results We identified 215 RCTs. A total of 43 were excluded for the following reasons: They were subgroup analyses or follow-up studies of previously reported RCTs (n = 24), the unit of randomization was not individual persons (n = 11), multiple studies were reported simultaneously (n = 5), diagnostic strategies were investigated (n = 2), or in vitro methods were used (n = 1). The analysis comprised the remaining 172 RCTs (Table 2). The median number of participants was 257 (range, 18 to 54 654). Approximately two thirds of the studies were carried out in several settings (multicenter), and about half were sponsored by industry. Pharmaceutical agents (70% of the studies) were by far the most common intervention used. Table 2. Reporting of Enrollment Process by Study Characteristic Reporting the Recruitment Process About one half of the published RCTs (90 of 172) reported information about the number of potential participants that were screened by the investigators for eligibility; the rate of reporting did not differ across the four journals (Table 2). We found no significant association between reporting the number of people screened and the size of the study (number of participants) or whether trials were multicenter in design, industry sponsored, or performed by investigators outside the United States. However, we found that trials in which the mortality rate in the control group was less than or equal to 5% were significantly more likely to provide some screening information (59%) than other trials (37% and 40% for the intermediate and highest mortality groups, respectively) (P = 0.04). The number of people who were eligible for participation was reported in 74 studies (43%). Larger studies were less likely to report this information, although the difference was not significant. Multicenter trials were much less likely to report the number of eligible participants (34%) than were single-center trials (59%) (P = 0.002). Reporting this inf

Antihypertensive medications and serious fall injuries in a nationally representative sample of older adults

IMPORTANCE The effect of serious injuries, such as hip fracture and head injury, on mortality and function is comparable to that of cardiovascular events. Concerns have been raised about the risk of fall injuries in older adults taking antihypertensive medications. The low risk of fall injuries reported in clinical trials of healthy older adults may not reflect the risk in older adults with multiple chronic conditions. OBJECTIVE To determine whether antihypertensive medication use was associated with experiencing a serious fall injury in a nationally representative sample of older adults. DESIGN, PARTICIPANTS, AND SETTING Competing risk analysis as performed with propensity score adjustment and matching in the nationally representative Medicare Current Beneficiary Survey cohort during a 3-year follow-up through 2009. Participants included 4961 community-living adults older than 70 years with hypertension. EXPOSURES Antihypertensive medication intensity based on the standardized daily dose for each antihypertensive medication class that participants used. MAIN OUTCOMES AND MEASURES Serious fall injuries, including hip and other major fractures, traumatic brain injuries, and joint dislocations, ascertained through Centers for Medicare & Medicaid Services claims. RESULTS Of the 4961 participants, 14.1% received no antihypertensive medications; 54.6% were in the moderate-intensity and 31.3% in the high-intensity antihypertensive groups. During follow-up, 446 participants (9.0%) experienced serious fall injuries, and 837 (16.9%) died. The adjusted hazard ratios for serious fall injury were 1.40 (95% CI, 1.03-1.90) in the moderate-intensity and 1.28 (95% CI, 0.91-1.80) in the high-intensity antihypertensive groups compared with nonusers. Although the difference in adjusted hazard ratios across the groups did not reach statistical significance, results were similar in the propensity score-matched subcohort. Among 503 participants with a previous fall injury, the adjusted hazard ratios were 2.17 (95% CI, 0.98-4.80) for the moderate-intensity and 2.31 (95% CI, 1.01-5.29) for the high-intensity antihypertensive groups. CONCLUSIONS AND RELEVANCE Antihypertensive medications were associated with an increased risk of serious fall injuries, particularly among those with previous fall injuries. The potential harms vs benefits of antihypertensive medications should be weighed in deciding to continue treatment with antihypertensive medications in older adults with multiple chronic conditions.

Incidence of Heart Failure or Cardiomyopathy After Adjuvant Trastuzumab Therapy for Breast Cancer

OBJECTIVES The purpose of this study was to estimate heart failure (HF) and cardiomyopathy (CM) rates after adjuvant trastuzumab therapy and chemotherapy in a population of older women with early-stage breast cancer. BACKGROUND Newer biologic therapies for breast cancer such as trastuzumab have been reported to increase HF and CM in clinical trials, especially in combination with anthracycline chemotherapy. Elderly patients, however, typically have a higher prevalence of cardiovascular risk factors and have been underrepresented in trastuzumab clinical trials. METHODS Using Surveillance, Epidemiology, and End Results-Medicare data from 2000 through 2007, we identified women 67 to 94 years of age with early-stage breast cancer. We calculated 3-year incidence rates of HF or CM for the following mutually exclusive treatment groups: trastuzumab (with or without nonanthracycline chemotherapy), anthracycline plus trastuzumab, anthracycline (without trastuzumab and with or without nonanthracycline chemotherapy), other nonanthracycline chemotherapy, or no adjuvant chemotherapy or trastuzumab therapy. HF or CM events were ascertained from administrative Medicare claims. Poisson regression was used to quantify risk of HF or CM, adjusting for sociodemographic factors, cancer characteristics, and cardiovascular conditions. RESULTS We identified 45,537 older women (mean age: 76.2 years, standard deviation: 6.2 years) with early-stage breast cancer. Adjusted 3-year HF or CM incidence rates were higher for patients receiving trastuzumab (32.1 per 100 patients) and anthracycline plus trastuzumab (41.9 per 100 patients) compared with no adjuvant therapy (18.1 per 100 patients, p < 0.001). Adding trastuzumab to anthracycline therapy added 12.1, 17.9, and 21.7 HF or CM events per 100 patients over 1, 2, and 3 years of follow-up, respectively. CONCLUSIONS HF or CM are common complications after trastuzumab therapy for older women, with higher rates than those reported from clinical trials.

Participation in Surgical Oncology Clinical Trials: Gender-, Race/Ethnicity-, and Age-based Disparities

ObjectiveTo characterize the representation of racial/ethnic minorities, women, and older persons among participants in surgical trials sponsored by the National Cancer Institute (NCI).MethodsThe NCI Clinical Trial Cooperative Group surgical oncology trials database was queried for breast, colorectal, lung, and prostate cancers treated during the period 2000–2002 (n=13,991). Data from the SEER program and the Census were used to estimate age-, gender-, and race/ethnicity-specific incidence of the same cancers among U.S. adults during the same period. Enrollment fraction (EF), defined as the number of trial enrollees divided by the estimated U.S. cancer cases in each demographic group, was the primary outcome measure. Logistic regression was used to compare the enrollment of racial/ethnic, gender and age subgroups in this analysis.ResultsRelative to white patients (EF=0.72%), lower EFs were noted in African-American (0.48%, odds ratio[OR] vs whites 0.67, P<0.001), Hispanic (0.54%, OR 0.76, P<0.001), and Asian/Pacific islander (0.59%, OR 0.82, P=0.001) patients. Overall, women were more likely to enroll in surgical trials (1.12%) than men (0.22%, OR 5.06, P<0.001). Patients 65–74 years of age (EF 0.45%) were less likely to be enrolled than those 20–44 years of age (EF=2.28%, OR 0.20, P=0.001).ConclusionsThe enrollment in surgical oncology trials is very low across all demographics. However, racial/ethnic minorities and older persons are less likely to be enrolled in cooperative group surgical oncology trials than are whites and younger patients. The high EF for women is due to the high availability of trials for women with breast cancer. Strategies to increase accrual to surgical trials and ameliorate disparities related to race/ethnicity, gender, and age are needed.

Use of Hospital-Based Acute Care Among Patients Recently Discharged From the Hospital

IMPORTANCE Current efforts to improve health care focus on hospital readmission rates as a marker of quality and on the effectiveness of transitions in care during the period after acute care is received. Emergency department (ED) visits are also a marker of hospital-based acute care following discharge but little is known about ED use during this period. OBJECTIVES To determine the degree to which ED visits and hospital readmissions contribute to overall use of acute care services within 30 days of discharge from acute care hospitals, to describe the reasons patients return for ED visits, and to describe these patterns among Medicare beneficiaries and those not covered by Medicare insurance. DESIGN, SETTING, AND PARTICIPANTS Prospective study of patients aged 18 years or older (mean age: 53.4 years) who were discharged between July 1, 2008, and September 31, 2009, from acute care hospitals in 3 large, geographically diverse states (California, Florida, and Nebraska) with data recorded in the Healthcare Cost and Utilization Project state inpatient and ED databases. MAIN OUTCOME MEASURES The 3 primary outcomes during the 30-day period after hospital discharge were ED visits not resulting in admission (treat-and-release encounters), hospital readmissions from any source, and a combined measure of ED visits and hospital readmissions termed hospital-based acute care. RESULTS The final cohort included 5,032,254 index hospitalizations among 4,028,555 unique patients. In the 30 days following discharge, 17.9% (95% CI, 17.9%-18.0%) of hospitalizations resulted in at least 1 acute care encounter. Of these 1,233,402 postdischarge acute care encounters, ED visits comprised 39.8% (95% CI, 39.7%-39.9%). For every 1000 discharges, there were 97.5 (95% CI, 97.2-97.8) ED treat-and-release visits and 147.6 (95% CI, 147.3-147.9) hospital readmissions in the 30 days following discharge. The number of ED treat-and-release visits ranged from a low of 22.4 (95% CI, 4.6-65.4) encounters per 1000 discharges for breast malignancy to a high of 282.5 (95% CI, 209.7-372.4) encounters per 1000 discharges for uncomplicated benign prostatic hypertrophy. Among the highest volume discharges, the most common reason patients returned to the ED was always related to their index hospitalization. CONCLUSIONS AND RELEVANCE After discharge from acute care hospitals in 3 states, ED visits within 30 days were common among adults and accounted for 39.8% of postdischarge hospital-based acute care visits. Improving care transitions should focus not only on decreasing readmissions but also on ED visits.

Multimorbidity and Survival in Older Persons with Colorectal Cancer

OBJECTIVES: To ascertain the effect of common chronic conditions on mortality in older persons with colorectal cancer.