Richard N. Ross

Comparison of Clinical Outcomes for Women and Men after Acute Myocardial Infarction

Drugs Generic Name Brand Name alteplase Activase Abbreviations rt-PA = recombinant tissue plasminogen activator The decline in coronary heart disease-related deaths, which began in the mid-1960s [1-6], has been greater for men than for women [4]. Data from several large epidemiologic [7] and clinical [8-12] studies suggest that the prognosis after acute myocardial infarction is worse for women. Some investigators relate these differences to age, risk factor profile, and the severity of preexisting coronary disease [10-15], whereas others relate them to sex [8, 9, 12]. Epidemiologic research on coronary heart disease among women has been limited, particularly in the thrombolytic era. Although several population- and community-based studies have been done [7, 10, 14-16], different methods, diagnostic criteria, end points, and definitions have made direct comparisons between women and men difficult and unreliable. The Thrombolysis in Myocardial Infarction Phase II (TIMI-II) trial [17] provides a valuable opportunity to investigate the potential influence of sex on clinical outcome after myocardial infarction. In a secondary observational analysis, we assessed possible differences in morbidity and mortality between men and women with myocardial infarction treated with thrombolytic therapy. We also analyzed the relation of any differences to baseline patient characteristics and clinical features. Methods Patient Selection Details of the TIMI-II protocol have been reported before [17, 18]. Briefly, women and men younger than 76 years who had ischemic chest pain lasting 30 minutes or more, in whom treatment with recombinant tissue plasminogen activator (rt-PA) (alteplase; Activase, Genentech, South San Francisco, California) within 4 hours of symptom onset was feasible, were considered for the study. Exclusion criteria included a history of cerebrovascular disease; blood pressure greater than 180 mm Hg systolic or 110 mm Hg diastolic; systemic bleeding disorders; major surgery within the previous 2 weeks; recent prolonged cardiopulmonary resuscitation; percutaneous transluminal coronary angioplasty or severe trauma within the previous 6 months; previous coronary artery bypass grafting or prosthetic heart valve replacement; left bundle-branch block; dilated cardiomyopathy; and other serious illness. Thrombolytic Therapy The rt-PA used in the TIMI-II study was produced by the suspension culture method (G11044, supplied by Genentech). The total dosage of rt-PA used in the first 520 patients was 150 mg administered intravenously during a period of 6 hours. Because of an unacceptably high rate of intracranial hemorrhage [19], however, the dosage was reduced to 100 mg given during 6 hours in the remaining patients. Assigned Strategies and Beta-Blocker Treatment Patients were assigned randomly to receive one of two treatment regimens: 1) routine coronary angiography done 18 to 48 hours after study entry and percutaneous transluminal coronary angioplasty or coronary artery bypass grafting if angiography showed that the patients anatomy was suitable [invasive strategy]; or 2) conventional care without coronary angiography and percutaneous transluminal coronary angioplasty, unless evidence showed either spontaneous or exercise-induced myocardial ischemia (conservative strategy) [17]. Coronary artery bypass grafting was done in patients assigned to either group for appropriate clinical indications. In the TIMI-IIA substudy [18], 195 patients were assigned to receive an immediate invasive strategy and were excluded from the analysis. Enrollment of patients in TIMI-IIB (the -blocker substudy) [20] at the seven TIMI-IIA clinical sites did not begin until enrollment in TIMI-IIA was completed. In TIMI-IIB, patients assigned to receive immediate intravenous -blocker therapy were given 15 mg of metoprolol as three 5-mg intravenous injections at 2-minute intervals, followed by oral metoprolol. Those assigned to receive deferred -blocker therapy received 50 mg of oral metoprolol twice on day 6 and 100 mg twice each day thereafter. Concomitant Care Patients received intravenous lidocaine for 24 hours and intravenous heparin for 5 days. Aspirin (80 mg) was administered on the day of study entry according to the protocol in the first 488 patients and on the next day in the remaining patients; it was increased to 325 mg per day on day 6, when intravenous heparin was replaced by subcutaneous heparin. End Points The primary end point in TIMI-II was survival with no recurrent myocardial infarction at 42 days. Secondary end points included the ejection fraction at rest and during exercise at hospital discharge and at 6 weeks. Complications of therapy were also assessed. Follow-up examinations were conducted 6 weeks and 1 year after study entry. The vital status of all patients not individually examined was determined by telephone interview. Statistical Analysis Probability values and confidence intervals for percentages and proportions were calculated using standard methods to test differences between two independent proportions [21, 22]. Because of multiple comparisons in the TIMI-II secondary analyses, probability values between 0.01 and 0.001 for two-sided tests were considered to provide some evidence of differences, and values less than 0.001 were thought to provide strong evidence of differences. Comparisons between mortality and either mortality or myocardial infarction rates are based on Cox regression analysis [23, 24]. The Cox proportional-hazards model was examined for validity of assumptions using the Kaplan-Meier [23] estimates of survival (S[t]) for each covariate in graphs plotting the log (log[S(t)]) against time to events (death and death or myocardial infarction), and the assumptions were tested for the comparison of men with women by introducing time-dependent variables for interaction [24]. Adjustment, when appropriate, was made for assignment to conservative or invasive strategy, rt-PA dose, and the TIMI-II baseline patient characteristics (age, previous myocardial infarction, anterior myocardial infarction, history of diabetes, history of hypertension, time from onset of symptoms to study entry, ongoing chest pain when rt-PA infusion was begun, history of congestive heart failure, race, and history of angina). Crude event rates and Kaplan-Meier event rates for mortality and for death or myocardial infarction were almost identical because of the completeness of follow-up information. Tests of interaction were done using crude event rates and the Breslow-Day statistic [25]. This report is based on an analysis file prepared at the TIMI Coordinating Center in January 1991. Results Patient Characteristics Women were older than men, with mean ages of 62.2 and 56.6 years (P < 0.001), respectively, and more commonly had past medical histories that included congestive heart failure (P < 0.001), systemic hypertension (P < 0.001), or diabetes mellitus (P < 0.001). As a group, women were less likely than men to be classified as low risk (P < 0.001). The time from symptom onset to study entry was delayed in women compared with men (2.8 hours compared with 2.6 hours; P < 0.001). Fewer women than men were considered eligible for the -blocker study (P < 0.001) (Table 1). Invasive Procedures and Medical Treatments The frequency of invasive procedures done within 6 weeks of study entry is summarized in Table 2. No differences between men and women were found in either the invasive or conservative treatment groups. Throughout this period, women were less likely than men to receive -blockers, but calcium channel blockers were prescribed more frequently for women. Aspirin was used with similar frequency. Table 1. Baseline Characteristics and Clinical Features of Patients* Complications Coronary Angioplasty Although coronary arterial dissection was observed more frequently in women than in men (17.2% compared with 10.0%; P = 0.002), within 24 hours after percutaneous transluminal coronary angioplasty, the frequencies of recurrent myocardial infarction, death, or the need to do emergent coronary bypass surgery did not differ statistically between women and men assigned to receive invasive procedures. Sex was not associated with the frequency of successful percutaneous transluminal coronary angioplasty [26]. Left Ventricular Function More of the 597 women in the TIMI-II study had resting left ventricular ejection fractions greater than 55% on radionuclide ventriculography than did the 2742 men before hospital discharge (33.5% compared with 29.0%; P = 0.03) and at 6-week follow-up (32.8% compared with 27.1%; P = 0.005). However, a greater proportion of these women than men did not have radionuclide studies analyzed because of death or inability to measure ejection fraction at hospital discharge (24.0% compared with 16.6%; P < 0.001) and 6-week follow-up (34.2% compared with 25.5%; P < 0.001). Patient Outcome: Mortality and Morbidity One-year follow-up data were available for 3316 (99.3%) patients [27]. Event rates according to sex and treatment strategy are summarized in Table 3. The cumulative 6-week mortality rate was higher for women than for men (9% compared with 4%; P < 0.001). Combined reinfarction and death also was more common among women than men (15.9% compared with 9.5%; P < 0.001). These differences (for both the invasive and conservative treatments) persisted at 1-year follow-up (Figures 1 and 2). Table 2. Invasive Procedures and Medications at 6 Weeks from Study Entry according to Sex and Treatment Strategy* Figure 1. One-year Kaplan-Meier mortality curves for women and men. Figure 2. One-year Kaplan-Meier event rates for reinfarction in women and men. The occurrence of myocardial infarction or death was predictably lower for low-risk women and men. The mortality rate was 1.9% for women compared with 1.6% for men (P = 0.78) 6 weeks after study entry, and it was 3.1% compared with 2.5% (P = 0.66) 1 year after study entry. Among high

Comparing the Contributions of Groups of Predictors: Which Outcomes Vary with Hospital Rather than Patient Characteristics?

Abstract In a model, such as a logit regression model, we wish to compare the relative importance of two groups of predictors for various objectives. In the example that motivated this work, the model predicts patient outcomes during hospital stays, and we wish to measure the relative contribution of patient and hospital characteristics to the variation in outcomes among patients and among hospitals. This is done using the relative dispersion of patient and hospital contributions to the fitted outcomes. As is seen, this question is distinct from other common questions, including the quality of the overall fit, the degree to which the outcome is accurately predicted, the statistical significance of groups of predictors, and the correlations among and between groups of predictors. Relevant point estimates, confidence intervals, and hypothesis tests are developed. In the example, we examine three outcome measures and find that nearly all of the predictable variation in patient outcomes and most of the predic...

Characteristics Associated With Differences in Survival Among Black and White Women With Breast Cancer

IMPORTANCE Difference in breast cancer survival by race is a recognized problem among Medicare beneficiaries. OBJECTIVE To determine if racial disparity in breast cancer survival is primarily attributable to differences in presentation characteristics at diagnosis or subsequent treatment. DESIGN, SETTING, AND PATIENTS Comparison of 7375 black women 65 years and older diagnosed between 1991 to 2005 and 3 sets of 7375 matched white control patients selected from 99,898 white potential controls, using data for 16 US Surveillance, Epidemiology and End Results (SEER) sites in the SEER-Medicare database. All patients received follow-up through December 31, 2009, and the black case patients were matched to 3 white control populations on demographics (age, year of diagnosis, and SEER site), presentation (demographics variables plus patient comorbid conditions and tumor characteristics such as stage, size, grade, and estrogen receptor status), and treatment (presentation variables plus details of surgery, radiation therapy, and chemotherapy). MAIN OUTCOMES AND MEASURES 5-Year survival. RESULTS The absolute difference in 5-year survival (blacks, 55.9%; whites, 68.8%) was 12.9% (95% CI, 11.5%-14.5%; P < .001) in the demographics match. This difference remained unchanged between 1991 and 2005. After matching on presentation characteristics, the absolute difference in 5-year survival was 4.4% (95% CI, 2.8%-5.8%; P < .001) and was 3.6% (95% CI, 2.3%-4.9%; P < .001) lower for blacks than for whites matched also on treatment. In the presentation match, fewer blacks received treatment (87.4% vs 91.8%; P < .001), time from diagnosis to treatment was longer (29.2 vs 22.8 days; P < .001), use of anthracyclines and taxols was lower (3.7% vs 5.0%; P < .001), and breast-conserving surgery without other treatment was more frequent (8.2% vs 7.3%; P = .04). Nevertheless, differences in survival associated with treatment differences accounted for only 0.81% of the 12.9% survival difference. CONCLUSIONS AND RELEVANCE In the SEER-Medicare database, differences in breast cancer survival between black and white women did not substantially change among women diagnosed between 1991 and 2005. These differences in survival appear primarily related to presentation characteristics at diagnosis rather than treatment differences.

Minimum Distance Matched Sampling With Fine Balance in an Observational Study of Treatment for Ovarian Cancer

In observational studies of treatment effects, matched samples have traditionally been constructed using two tools, namely close matches on one or two key covariates and close matches on the propensity score to stochastically balance large numbers of covariates. Here we propose a third tool, fine balance, obtained using the assignment algorithm in a new way. We use all three tools to construct a matched sample for an ongoing study of provider specialty in the treatment of ovarian cancer. Fine balance refers to exact balance of a nominal covariate, often one with many categories, but it does not require individually matched treated and control subjects for this variable. In the example the nominal variable has 72 = 9 × 8 categories formed from 9 possible years of diagnosis and 8 geographic locations or SEER sites. We obtain exact balance on the 72 categories and close individual matches on clinical stage, grade, year of diagnosis, and other variables using a distance, and stochastically balance a total of 61 covariates using a propensity score. Our approach finds an optimal match that minimizes a suitable distance subject to the constraint that fine balance is achieved. This is done by defining a special patterned distance matrix and passing it to a subroutine that solves the optimal assignment problem, which optimally pairs the rows and columns of a matrix using a polynomial time algorithm. In the example we used the function Proc Assign in SAS. A new theorem shows that with our patterned distance matrix, the assignment algorithm returns an optimal, finely balanced matched sample whenever one exists, and otherwise returns an infinite distance, indicating that no such matched sample exists.

Association of the 2011 ACGME Resident Duty Hour Reforms With Mortality and Readmissions Among Hospitalized Medicare Patients

IMPORTANCE Patient outcomes associated with the 2011 Accreditation Council for Graduate Medical Education (ACGME) duty hour reforms have not been evaluated at a national level. OBJECTIVE To evaluate the association of the 2011 ACGME duty hour reforms with mortality and readmissions. DESIGN, SETTING, AND PARTICIPANTS Observational study of Medicare patient admissions (6,384,273 admissions from 2,790,356 patients) to short-term, acute care, nonfederal hospitals (n = 3104) with principal medical diagnoses of acute myocardial infarction, stroke, gastrointestinal bleeding, or congestive heart failure or a Diagnosis Related Group classification of general, orthopedic, or vascular surgery. Of the hospitals, 96 (3.1%) were very major teaching, 138 (4.4%) major teaching, 442 (14.2%) minor teaching, 443 (14.3%) very minor teaching, and 1985 (64.0%) nonteaching. EXPOSURE Resident-to-bed ratio as a continuous measure of hospital teaching intensity. MAIN OUTCOMES AND MEASURES Change in 30-day all-location mortality and 30-day all-cause readmission, comparing patients in more intensive relative to less intensive teaching hospitals before (July 1, 2009-June 30, 2011) and after (July 1, 2011-June 30, 2012) duty hour reforms, adjusting for patient comorbidities, time trends, and hospital site. RESULTS In the 2 years before duty hour reforms, there were 4,325,854 admissions with 288,422 deaths and 602,380 readmissions. In the first year after the reforms, accounting for teaching hospital intensity, there were 2,058,419 admissions with 133,547 deaths and 272,938 readmissions. There were no significant postreform differences in mortality accounting for teaching hospital intensity for combined medical conditions (odds ratio [OR], 1.00; 95% CI, 0.96-1.03), combined surgical categories (OR, 0.99; 95% CI, 0.94-1.04), or any of the individual medical conditions or surgical categories. There were no significant postreform differences in readmissions for combined medical conditions (OR, 1.00; 95% CI, 0.97-1.02) or combined surgical categories (OR, 1.00; 95% CI, 0.98-1.03). For the medical condition of stroke, there were higher odds of readmissions in the postreform period (OR, 1.06; 95% CI, 1.001-1.13). However, this finding was not supported by sensitivity analyses and there were no significant postreform differences for readmissions for any other individual medical condition or surgical category. CONCLUSIONS AND RELEVANCE Among Medicare beneficiaries, there were no significant differences in the change in 30-day mortality rates or 30-day all-cause readmission rates for those hospitalized in more intensive relative to less intensive teaching hospitals in the year after implementation of the 2011 ACGME duty hour reforms compared with those hospitalized in the 2 years before implementation.

Medical and financial risks associated with surgery in the elderly obese.

Objective: To study the medical and financial outcomes associated with surgery in elderly obese patients and to ask if obesity itself influences outcomes above and beyond the effects from comorbidities that are known to be associated with obesity. Background: Obesity is a surgical risk factor not present in Medicares risk adjustment or payment algorithms, as BMI is not collected in administrative claims. Methods: A total of 2045 severely or morbidly obese patients (BMI ≥ 35 kg/m2, aged between 65 and 80 years) selected from 15,914 elderly patients in 47 hospitals undergoing hip and knee surgery, colectomy, and thoracotomy were matched to 2 sets of 2045 nonobese patients (BMI = 20–30 kg/m2). A “limited match” controlled for age, sex, race, procedure, and hospital. A “complete match” also controlled for 30 additional factors such as diabetes and admission clinical data from chart abstraction. Results: Mean BMI in the obese patients was 40 kg/m2 compared with 26 kg/m2 in the nonobese. In the complete match, obese patients displayed increased odds of wound infection: OR (odds ratio) = 1.64 (95% CI: 1.21, 2.21); renal dysfunction: OR = 2.05 (1.39, 3.05); urinary tract infection: OR = 1.55 (1.24, 1.94); hypotension: OR = 1.38 (1.07, 1.80); respiratory events: OR = 1.44 (1.19, 1.75); 30-day readmission: OR = 1.38 (1.08, 1.77); and a 12% longer length of stay (8%, 17%). Provider costs were 10% (7%, 12%) greater in obese than in nonobese patients, whereas Medicare payments increased only 3% (2%, 5%). Findings were similar in the limited match. Conclusions: Obesity increases the risks and costs of surgery. Better approaches are needed to reduce these risks. Furthermore, to avoid incentives to underserve this population, Medicare should consider incorporating incremental costs of caring for obese patients into payment policy and include obesity in severity adjustment models.

Does Ovarian Cancer Treatment and Survival Differ by the Specialty Providing Chemotherapy

PURPOSE Chemotherapy for ovarian cancer is usually administered by medical oncologists (MOs) or gynecologic oncologists (GOs). GOs perform a broad spectrum of surgical and medical activities while managing a limited number of diseases; MOs specialize in the administration of chemotherapy but manage a broad array of diseases. We asked whether survival, treatment, and toxicity differed according to the type of specialist providing the chemotherapy after surgery. PATIENTS AND METHODS Using Surveillance, Epidemiology, and End Results (SEER)--Medicare data for patients 65 years old from 1991 through 2001 from eight SEER sites, we identified 344 patients with ovarian cancer who were treated with chemotherapy by a GO after surgery. Using optimal matching and propensity scores based on 36 characteristics, we matched these patients to 344 similar patients who were operated on and staged by the same type of surgeon but who received chemotherapy from an MO. RESULTS MOs administered chemotherapy over more weeks than did the GOs (16.5 v 12.1 weeks, respectively; P < .0023), and MO patients had substantially more weeks that included chemotherapy-associated adverse events than GO patients (16.2 v 8.9 weeks, respectively; P < .0001). However, there was no difference in 5-year survival rate between the GO and MO groups (35% v 34%, respectively; P = .45). CONCLUSION GO- and MO-treated patients who were closely matched on prognostic characteristics experienced very different rates of chemotherapy-associated adverse events and very different chemotherapy treatment styles by specialty type; however, their survival was virtually identical.

The Hospital Compare Mortality Model and the Volume–Outcome Relationship

OBJECTIVE We ask whether Medicares Hospital Compare random effects model correctly assesses acute myocardial infarction (AMI) hospital mortality rates when there is a volume-outcome relationship. DATA SOURCES/STUDY SETTING Medicare claims on 208,157 AMI patients admitted in 3,629 acute care hospitals throughout the United States. STUDY DESIGN We compared average-adjusted mortality using logistic regression with average adjusted mortality based on the Hospital Compare random effects model. We then fit random effects models with the same patient variables as in Medicares Hospital Compare mortality model but also included terms for hospital Medicare AMI volume and another model that additionally included other hospital characteristics. PRINCIPAL FINDINGS Hospital Compares average adjusted mortality significantly underestimates average observed death rates in small volume hospitals. Placing hospital volume in the Hospital Compare model significantly improved predictions. CONCLUSIONS The Hospital Compare random effects model underestimates the typically poorer performance of low-volume hospitals. Placing hospital volume in the Hospital Compare model, and possibly other important hospital characteristics, appears indicated when using a random effects model to predict outcomes. Care must be taken to insure the proper method of reporting such models, especially if hospital characteristics are included in the random effects model.

Inpatient rehabilitation after stroke: a comparison of lengths of stay and outcomes in the Veterans Affairs and non-Veterans Affairs health care system.

Background.Patients have longer lengths of hospital stay (LOS) in VA medical centers than in the general health care system. Objective.The objective of this study was to determine whether resource use and outcome differences between VA and non-VA inpatient rehabilitation facilities remain after controlling for patient and medical care delivery differences. Design.This analysis involved 60 VA inpatient rehabilitation units and 467 non-VA rehabilitation hospitals and units. Multivariate adjusted resource use and patient outcome differences were compared across setting within patients grouped by severity of disability at admission through assignment to the Function Related Group (FRG) patient classification system. Subjects.The study included 55,438 stroke patients. Measures.Study measures were LOS, functional status at discharge, and community discharge. Results.The VA serves a higher proportion of patients who are single, separated, or divorced; are unemployed or retired as a result of disability, and are not white (P <0.0001). These traits tended to be associated with longer LOS, lower functional outcomes, and reduced rates of community discharge. After adjusting for these and other differences, depending on FRG, average LOS remained from 30% to 200% longer in the VA centers (P <0.05); average functional outcomes were significantly higher in 8 and lower in 2 FRGs (P <0.05); and community discharge rates were lower in 12 FRGs (P <0.05). Conclusions.While certain variables accounted for some of the observed differences in resource use and outcomes, differences remained after adjustment. Fewer incentives for cost containment and less support in patients’ home environments may be among the most important unmeasured determinants of VA differences.

Risks of acute hospital transfer and mortality during stroke rehabilitation.

OBJECTIVE To identify demographic, medical, and functional factors associated with transfer of stroke patients to acute hospital services and/or mortality during stroke rehabilitation. DESIGN Two case-control studies in which logistic regression was used to control for clinical traits associated with differences in likelihood. SETTING A total of 542 US inpatient and rehabilitation units. PARTICIPANTS A total of 64,471 patients discharged during 1995. INTERVENTIONS Not applicable. MAIN OUTCOME MEASURES Transfer to an acute hospital service and death. RESULTS There were 5847 (9.1%) acute hospital transfers and 320 (0.5%) deaths. Greater disability at admission was associated with higher odds of both acute hospitalization and mortality. Cardiopulmonary arrest, chest pain, gastrointestinal problems, bleeding disorders, hypercoagulable states, and acute renal difficulties increased the relative odds of acute hospitalization from 3.1 (95% confidence interval [CI], 2.3-4.2) to 12.7 (95% CI, 9.2-17.6). The likelihood of mortality for patients 85 years of age or older was more than 2-fold (2.5; 95% CI, 1.7-3.6) that of patients 65 years of age or younger for blacks, it was nearly 2-fold (1.7; 95% CI, 1.3-2.3) compared with whites, after adjusting for clinical differences. CONCLUSION Higher likelihoods of mortality among older patients versus younger, black patients versus white, and patients with more rather than less disability at admission suggest the need for greater vigilance in monitoring medical status.