ABSTRACT
In stepped wedge designs (SWD), clusters are randomized to the time period during which new patients will receive the intervention under study in a sequential rollout over time. By the study's end, patients at all clusters receive the intervention, eliminating ethical concerns related to withholding potentially efficacious treatments. This is a practical option in many large-scale public health implementation settings. Little statistical theory for these designs exists for binary outcomes. To address this, we utilized a maximum likelihood approach and developed numerical methods to determine the asymptotic power of the SWD for binary outcomes. We studied how the power of a SWD for detecting risk differences varies as a function of the number of clusters, cluster size, the baseline risk, the intervention effect, the intra-cluster correlation coefficient, and the time effect. We studied the robustness of power to the assumed form of the distribution of the cluster random effects, as well as how power is affected by variable cluster size. % SWD power is sensitive to neither, in contrast to the parallel cluster randomized design which is highly sensitive to variable cluster size. We also found that the approximate weighted least square approach of Hussey and Hughes (2007, Design and analysis of stepped wedge cluster randomized trials. Contemporary Clinical Trials 28, 182-191) for binary outcomes under-estimates the power in some regions of the parameter spaces, and over-estimates it in others. The new method was applied to the design of a large-scale intervention program on post-partum intra-uterine device insertion services for preventing unintended pregnancy in the first 1.5 years following childbirth in Tanzania, where it was found that the previously available method under-estimated the power.
Subject(s)
Data Interpretation, Statistical , Models, Statistical , Outcome Assessment, Health Care/methods , Humans , Likelihood FunctionsABSTRACT
PURPOSE: We sought to evaluate the association of prolonged elevated heart rate (peHR) with survival in acutely ill patients. METHODS: We used a large observational intensive care unit (ICU) database (Multiparameter Intelligent Monitoring in Intensive Care III [MIMIC-III]), where frequent heart rate measurements were available. The peHR was defined as a heart rate >100 beats/min in 11 of 12 consecutive hours. The outcome was survival status at 90 days. We collected heart rates, disease severity (simplified acute physiology scores [SAPS II]), comorbidities (Charlson scores), and International Classification of Diseases (ICD) diagnosis information in 31 513 patients from the MIMIC-III ICU database. Propensity score (PS) methods followed by inverse probability weighting based on the PS was used to balance the 2 groups (the presence/absence of peHR). Multivariable weighted logistic regression was used to assess for association of peHR with the outcome survival at 90 days adjusting for additional covariates. RESULTS: The mean age was 64 years, and the most frequent main disease category was circulatory disease (41%). The mean SAPS II score was 35, and the mean Charlson comorbidity score was 2.3. Overall survival of the cohort at 90 days was 82%. Adjusted logistic regression showed a significantly increased risk of death within 90 days in patients with an episode of peHR (P < .001; odds ratio for death 1.79; confidence interval, 1.69-1.88). This finding was independent of median heart rate. CONCLUSION: We found a significant association of peHR with decreased survival in a large and heterogenous cohort of ICU patients.
Subject(s)
Critical Illness/mortality , Tachycardia/mortality , Acute Disease , Adult , Aged , Critical Care , Databases, Factual , Female , Follow-Up Studies , Humans , Intensive Care Units , Logistic Models , Male , Middle Aged , Monitoring, Physiologic , Multivariate Analysis , Prognosis , Tachycardia/diagnosis , Time FactorsABSTRACT
We investigate different primary efficacy analysis approaches for a 2-armed randomized clinical trial when interest is focused on a time to event primary outcome that is subject to a competing risk. We extend the work of Friedlin and Korn (2005) by considering estimation as well as testing and by simulating the primary and competing events' times from both a cause-specific hazards model as well as a joint subdistribution-cause-specific hazards model. We show that the cumulative incidence function can provide useful prognostic information for a particular patient but is not advisable for the primary efficacy analysis. Instead, it is preferable to fit a Cox model for the primary event which treats the competing event as an independent censoring. This is reasonably robust for controlling type I error and treatment effect bias with respect to the true primary and competing events' cause-specific hazards model, even when there is a shared, moderately prognostic, unobserved baseline frailty for the primary and competing events in that model. However, when it is plausible that a strongly prognostic frailty exists, combining the primary and competing events into a composite event should be considered. Finally, when there is an a priori interest in having both the primary and competing events in the primary analysis, we compare a bivariate approach for establishing overall treatment efficacy to the composite event approach. The ideas are illustrated by analyzing the Women's Health Initiative clinical trials sponsored by the National Heart, Lung, and Blood Institute.
ABSTRACT
BACKGROUND: Changes in adaptive immune cells after chemotherapy in adult acute myeloid leukemia (AML) may have implications for the success of immunotherapy. This study was designed to determine the functional capacity of the immune system in adult patients with AML who have completed chemotherapy and are potential candidates for immunotherapy. METHODS: We used the response to seasonal influenza vaccination as a surrogate for the robustness of the immune system in 10 AML patients in a complete remission post-chemotherapy and performed genetic, phenotypic, and functional characterization of adaptive immune cell subsets. RESULTS: Only 2 patients generated protective titers in response to vaccination, and a majority of patients had abnormal frequencies of transitional and memory B-cells. B-cell receptor sequencing showed a B-cell repertoire with little evidence of somatic hypermutation in most patients. Conversely, frequencies of T-cell populations were similar to those seen in healthy controls, and cytotoxic T-cells demonstrated antigen-specific activity after vaccination. Effector T-cells had increased PD-1 expression in AML patients least removed from chemotherapy. CONCLUSION: Our results suggest that while some aspects of cellular immunity recover quickly, humoral immunity is incompletely reconstituted in the year following intensive cytotoxic chemotherapy for AML. The observed B-cell abnormalities may explain the poor response to vaccination often seen in AML patients after chemotherapy. Furthermore, the uncoupled recovery of B-cell and T-cell immunity and increased PD-1 expression shortly after chemotherapy might have implications for the success of several modalities of immunotherapy.
Subject(s)
B-Lymphocytes/immunology , Immunity , Leukemia, Myeloid, Acute/drug therapy , Leukemia, Myeloid, Acute/immunology , Adult , Aged , Antibodies, Viral/immunology , Consolidation Chemotherapy , Demography , Female , Humans , Immunologic Memory , Influenza Vaccines/immunology , Lymphocyte Count , Male , Middle Aged , Programmed Cell Death 1 Receptor/metabolism , Remission Induction , T-Lymphocytes/immunology , Time Factors , Tissue Donors , Treatment Outcome , VaccinationABSTRACT
Modeling events requires accounting for differential follow-up duration, especially when combining randomized and observational studies. Although events occur at any point over a follow-up period and censoring occurs throughout, most applied researchers use odds ratios as association measures, assuming follow-up duration is similar across treatment groups. We derive the bias of the rate ratio when incorrectly assuming equal follow-up duration in the single study binary treatment setting. Simulations illustrate bias, efficiency, and coverage and demonstrate that bias and coverage worsen rapidly as the ratio of follow-up duration between arms moves away from one. Combining study rate ratios with hierarchical Poisson regression models, we examine bias and coverage for the overall rate ratio via simulation in three cases: when average arm-specific follow-up duration is available for all studies, some studies, and no study. In the null case, bias and coverage are poor when the study average follow-up is used and improve even if some arm-specific follow-up information is available. As the rate ratio gets further from the null, bias and coverage remain poor. We investigate the effectiveness of cardiac resynchronization therapy devices compared with those with cardioverter-defibrillator capacity where three of eight studies report arm-specific follow-up duration.
Subject(s)
Bias , Follow-Up Studies , Meta-Analysis as Topic , Cardiac Resynchronization Therapy Devices , Computer Simulation , Defibrillators, Implantable , Epidemiologic Methods , Equipment and Supplies , Humans , Odds Ratio , Poisson Distribution , Regression AnalysisABSTRACT
In this commentary, we argue that although randomization has many benefits, not all questions we seek to answer fit into a randomized setting. Our argument utilizes the clinical setting of carotid atherosclerosis management where specific clinical questions are answered by using a variety of comparative effectiveness designs. Observational studies should not be ruled out when designing studies to address questions of comparative effectiveness.
Subject(s)
Comparative Effectiveness Research/organization & administration , Randomized Controlled Trials as Topic/standardsABSTRACT
BACKGROUND: 81 million people face impoverishment from surgical costs every year. The majority of this impoverishment is attributable to the non-medical costs of care-for transportation, for food and for lodging. Of these, transportation is the largest, but because it is not viewed as an actual medical cost, it is frequently unaddressed. This paper examines the effect on surgical utilisation of paying for transportation. METHODS: A hierarchical logistic regression was performed on 2692 patients presenting for surgical care to a non-governmental organisation operating in the Republic of the Congo, Guinea and Madagascar. Controlling for distance from the hospital, age, gender, the need for air travel and time between appointments, the effect of payment for transportation on the surgical no-show rate was evaluated. RESULTS: After adjustment for observed confounders, paying for transportation drops the surgical no-show rate by 45% (OR 0.55; 95% CI 0.40 to 0.77; p<0.001). Age, delay between appointments and the number of hours travelled for surgery also predict surgical no-show. For 28% of no-show patients, the cost of transportation from their homes to a nearby predetermined pick-up point remained a barrier, even when transportation from the pick-up point to the hospital was free. CONCLUSION: Transportation costs are a significant barrier to surgical care in low-resource settings, and paying for it halves the no-show rate. This finding highlights that decreasing demand-side barriers to surgical care cannot be limited only to the removal of user fees.
ABSTRACT
PURPOSE: SPINK1 overexpression has been described in prostate cancer and is linked with poor prognosis in many cancers. The objective of this study was to characterize the association between SPINK1 overexpression and prostate cancer-specific survival. EXPERIMENTAL DESIGN: The study included 879 participants in the U.S. Physicians' Health Study and Health Professionals Follow-Up Study, diagnosed with prostate cancer (1983-2004) and treated by radical prostatectomy. Protein tumor expression of SPINK1 was evaluated by immunohistochemistry on tumor tissue microarrays. RESULTS: Seventy-four of 879 (8%) prostate cancer tumors were SPINK1 positive. Immunohistochemical data were available for PTEN, p-Akt, pS6, stathmin, androgen receptor (AR), and ERG (as a measure of the TMPRSS2:ERG translocation). Compared with SPINK1-negative tumors, SPINK1-positive tumors showed higher PTEN and stathmin expression, and lower expression of AR (P < 0.01). SPINK1 overexpression was seen in 47 of 427 (11%) ERG-negative samples and in 19 of 427 (4%) ERG-positive cases (P = 0.0003). We found no significant associations between SPINK1 status and Gleason grade or tumor stage. There was no association between SPINK1 expression and biochemical recurrence (P = 0.56). Moreover, there was no association between SPINK1 expression and prostate cancer mortality (there were 75 lethal cases of prostate cancer during a mean of 13.5 years follow-up; HR = 0.71; 95% confidence interval, 0.29-1.76). CONCLUSIONS: Our results suggest that SPINK1 protein expression may not be a predictor of recurrence or lethal prostate cancer amongst men treated by radical prostatectomy. SPINK1 and ERG protein expression do not seem to be entirely mutually exclusive, as some previous studies have suggested.
Subject(s)
Adenocarcinoma/pathology , Biomarkers, Tumor/analysis , Carrier Proteins/biosynthesis , Prostatic Neoplasms/pathology , Adenocarcinoma/mortality , Aged , Disease Progression , Humans , Immunohistochemistry , Male , Middle Aged , Neoplasm Recurrence, Local/mortality , Neoplasm Recurrence, Local/pathology , Proportional Hazards Models , Prostatectomy , Prostatic Neoplasms/mortality , Tissue Array Analysis , Trypsin Inhibitor, Kazal PancreaticABSTRACT
BACKGROUND: Whether the genomic rearrangement transmembrane protease, serine 2 (TMPRSS2):v-ets erythroblastosis virus E26 oncogene homolog (ERG) has prognostic value in prostate cancer is unclear. METHODS: Among men with prostate cancer in the prospective Physicians' Health and Health Professionals Follow-Up Studies, we identified rearrangement status by immunohistochemical assessment of ERG protein expression. We used Cox models to examine associations of ERG overexpression with biochemical recurrence and lethal disease (distant metastases or cancer-specific mortality). In a meta-analysis including 47 additional studies, we used random-effects models to estimate associations between rearrangement status and outcomes. RESULTS: The cohort consisted of 1,180 men treated with radical prostatectomy between 1983 and 2005. During a median follow-up of 12.6 years, 266 men experienced recurrence and 85 men developed lethal disease. We found no significant association between ERG overexpression and biochemical recurrence [hazard ratio (HR), 0.99; 95% confidence interval (CI), 0.78-1.26] or lethal disease (HR, 0.93; 95% CI, 0.61-1.43). The meta-analysis of prostatectomy series included 5,074 men followed for biochemical recurrence (1,623 events), and 2,049 men followed for lethal disease (131 events). TMPRSS2:ERG was associated with stage at diagnosis [risk ratio (RR)(≥T3 vs. T2), 1.23; 95% CI, 1.16-1.30) but not with biochemical recurrence (RR, 1.00; 95% CI, 0.86-1.17) or lethal disease (RR, 0.99; 95% CI, 0.47-2.09). CONCLUSIONS: These results suggest that TMPRSS2:ERG, or ERG overexpression, is associated with tumor stage but does not strongly predict recurrence or mortality among men treated with radical prostatectomy. IMPACT: This is the largest prospective cohort study to examine associations of ERG overexpression and lethal prostate cancer among men treated with radical prostatectomy.
Subject(s)
Gene Fusion , Prostatic Neoplasms/genetics , Serine Endopeptidases/genetics , Trans-Activators/genetics , Aged , Cohort Studies , Gene Rearrangement , Humans , Male , Middle Aged , Neoplasm Recurrence, Local/genetics , Neoplasm Staging , Prostatic Neoplasms/pathology , Prostatic Neoplasms/surgery , Transcriptional Regulator ERG , Treatment OutcomeABSTRACT
BACKGROUND: The bimodality of the age-incidence curve of Hodgkin lymphoma (HL) has been ascribed to the existence of subgroups with distinct etiologies. Frailty models can be usefully applied to age-incidence curves of cancer to aid the understanding of biological phenomena in these instances. The models imply that for a given disease, a minority of individuals are at high risk, compared with the low-risk majority. METHODS: Frailty modeling is applied to interpret HL incidence on the basis of population-based cancer registry data from the five Nordic countries for the period 1993 to 2007. There were a total of 8,045 incident cases and 362,843,875 person-years at risk in the study period. RESULTS: A bimodal frailty analysis provides a reasonable fit to the age-incidence curves, employing 2 prototype models, which differ by having the sex covariate included in the frailty component (model 1) or in the baseline Weibull hazard (model 2). Model 2 seemed to fit better with our current understanding of HL than model 1 for the male-to-female ratio, number of rate-limiting steps in the carcinogenic process, and proportion of susceptibles; whereas model 1 performed better related to the heterogeneity in HL among elderly males. CONCLUSION: The present analysis shows that HL age-incidence data are consistent with a bimodal frailty model, indicating that heterogeneity in cancer susceptibility may give rise to bimodality at the population level, although the individual risk remains simple and monotonically increasing by age. IMPACT: Frailty modeling adds to the existing body of knowledge on the heterogeneity in risk of acquiring HL.