Treatment Effects In Subgroups Research Articles

Combining multiple predictive markers in stratified medicine

Stratified medicine requires identifying predictive markers to determine differential treatment effects for subgroups. Ideally, these markers are then validated in prospective randomised trials. However, many of the methods for the analysis and validation of markers are based on there being a single marker. For example, a biomarker stratified trial design typically stratifies on a single binary marker. In many clinical scenarios, including recently funded MRC consortia, there are hypothesised to be multiple markers, often of different modalities such as clinical, genetic and imaging markers. One issue in identifying any predictive marker is that an interaction effect is additive to the main effects of both treatment and the marker, which are also included in the analysis model. With multiple markers, if the effect size of one marker is much larger than any others, it alone may be sufficient for stratification of the population. If not, it may be appropriate to combine all markers into one single predictive biomarker. Kraemer has proposed a method for combining multiple markers into a single combined measure, provided the markers are not highly correlated, which is likely when they share a common mechanism. We describe this approach, and extend it to account for multiple markers of different modalities and which are identified from different data sources. We will discuss the issue of choosing the appropriate scale of interaction (additive versus multiplicative), and how to incorporate multiple markers into prospective trial designs such as biomarker stratified designs.

Augmented case-only designs for randomized clinical trials with failure time endpoints.

Under suitable assumptions and by exploiting the independence between inherited genetic susceptibility and treatment assignment, the case-only design yields efficient estimates for subgroup treatment effects and gene-treatment interaction in a Cox model. However it cannot provide estimates of the genetic main effect and baseline hazards, that are necessary to compute the absolute disease risk. For two-arm, placebo-controlled trials with rare failure time endpoints, we consider augmenting the case-only design with random samples of controls from both arms, as in the classical case-cohort sampling scheme, or with a random sample of controls from the active treatment arm only. The latter design is motivated by vaccine trials for cost-effective use of resources and specimens so that host genetics and vaccine-induced immune responses can be studied simultaneously in a bigger set of participants. We show that these designs can identify all parameters in a Cox model and that the efficient case-only estimator can be incorporated in a two-step plug-in procedure. Results in simulations and a data example suggest that incorporating case-only estimators in the classical case-cohort design improves the precision of all estimated parameters; sampling controls only in the active treatment arm attains a similar level of efficiency.

Abstract S3-01: The TNT trial: A randomized phase III trial of carboplatin (C) compared with docetaxel (D) for patients with metastatic or recurrent locally advanced triple negative or BRCA1/2 breast cancer (CRUK/07/012)

Abstract Introduction: Subgroups within sporadic triple negative breast cancers (TNBCs) appear to share impaired DNA damage response mechanisms with BRCA1/2 mutation-associated breast cancers. This has been hypothesised to confer particular sensitivity to DNA-damaging platinum chemotherapy. The TNT trial, a randomized phase III trial in women with metastatic or recurrent locally advanced TNBC or BRCA1/2 mutation-associated breast cancer, aimed to test this hypothesis and examine treatment effect in biological subgroups. Patients & Methods: Eligible patients had either ER-, PR-, HER2- breast cancer or were known BRCA1/2 carriers (any ER/PR/HER2). Patients were randomized (1:1) to receive either C (AUC 6 q3wk) or D (100mg/m2 q3wk) for 6-8 cycles or until disease progression if sooner and could cross over to the alternative treatment on confirmed progression. Ineligible patients included those who had ECOG performance status >2, received adjuvant taxane therapy in the last 12 mths, any previous treatment with a platinum chemotherapy, or previous non-anthracycline chemotherapy for metastatic disease. For consenting patients a blood sample and archived tissue samples were obtained for BRCA1/2 genotyping and central biomarker analysis (primary tumour, lymph nodes and recurrent tumour biopsy if available) of subtypes within TNBC and biomarkers of DNA repair deficiency. The primary endpoint was RECIST objective tumour response up to cycle 6 of randomised treatment. Secondary endpoints included toxicity, progression free survival (PFS), time to progression and overall survival. TNT aimed to detect a 15% improvement in ORR with C compared to D, with planned target sample size range of 370-450 depending on assumed ORR in D patients (2-sided α=0.05, power=90%). 376 (188 C, 188 D) were recruited from 74 UK centres between Apr 08 and Mar 14. Results: A snapshot of the data was taken on 30/5/14 at which point 336 (89.4%) patients had experienced a PFS event, with overall median PFS time of 4.4 mths. Median age of patients was 55 yrs (IQR 48-63). 366/376 (97%) patients had TNBC of whom 18 were also known BRCA1/2 mutation carriers, with the remaining 10 patients receptor +ve and BRCA1/2 carriers. 338/376 (90%) had metastatic and 38/376 (10%) recurrent locally advanced disease. 53% had liver or lung metastases affecting the parenchyma and 34% had received previous adjuvant taxane therapy. Median time from initial diagnosis to entering TNT was 2.2 yrs (IQR 1.5-3.5). Primary tumour tissue has currently been received for 277 patients, blood from 286 patients and recurrent tumour tissue from 85 patients. Discussion: TNT will report evidence on the activity of single agent platinum chemotherapy compared with single agent taxane in patients with TNBC and BRCA1/2 associated breast cancer. Correlative analyses of BRCA1/2 mutation status, subtypes and DNA repair biomarkers will also be reported. TNT will be the first randomised trial to report the activity of platinum compared with standard chemotherapy within TNBC subtypes and in relation to BRCA1/2 mutation status and DNA repair biomarkers. Safety, tolerability and response to crossover treatment will also be presented. Citation Format: Andrew Tutt, Paul Ellis, Lucy Kilburn, Cheryl Gilett, Sarah Pinder, Jacinta Abraham, Sophie Barrett, Peter Barrett-Lee, Stephen Chan, Maggie Cheang, Mitch Dowsett, Lisa Fox, Patrycja Gazinska, Anita Grigoriadis, Alexander Gutin, Catherine Harper-Wynne, Matthew Hatton, Sarah Kernaghan, Jerry Lanchbury, James Morden, Julie Owen, Jyoti Parikh, Peter Parker, Nazneen Rahman, Rebecca Roylance, Adam Shaw, Ian Smith, Rose Thompson, Kirsten Timms, Holly Tovey, Andrew Wardley, Gregory Wilson, Mark Harries, Judith Bliss. The TNT trial: A randomized phase III trial of carboplatin (C) compared with docetaxel (D) for patients with metastatic or recurrent locally advanced triple negative or BRCA1/2 breast cancer (CRUK/07/012) [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr S3-01.

Optimal Marker-Adaptive Designs for Targeted Therapy Based on Imperfectly Measured Biomarkers

SummaryTargeted therapy revolutionizes the way that physicians treat cancer and other diseases, enabling them to select individualized treatment adaptively according to the patient's biomarker profile. The implementation of targeted therapy requires that the biomarkers are accurately measured, which may not always be feasible in practice. We propose two optimal marker-adaptive trial designs in which the biomarkers are subject to measurement errors. The first design focuses on a patient's individual benefit and minimizes the treatment assignment error so that each patient has the highest probability of being assigned to the treatment that matches his or her true biomarker status. The second design focuses on the group benefit, which maximizes the overall response rate for all the patients enrolled in the trial. We develop a Wald test to evaluate the treatment effects for marker subgroups at the end of the trial and derive the corresponding asymptotic power function. Simulation studies and an application to a lymphoma cancer trial show that the optimal designs proposed achieve our design goal and obtain desirable operating characteristics.

Aspirin for the prevention of recurrent venous thromboembolism: the INSPIRE collaboration.

In patients with a first unprovoked venous thromboembolism (VTE) the risk of recurrent VTE remains high after anticoagulant treatment is discontinued. The Aspirin for the Prevention of Recurrent Venous Thromboembolism (the Warfarin and Aspirin [WARFASA]) and the Aspirin to Prevent Recurrent Venous Thromboembolism (ASPIRE) trials showed that aspirin reduces this risk, but they were not individually powered to detect treatment effects for particular outcomes or subgroups. An individual patient data analysis of these trials was planned, before their results were known, to assess the effect of aspirin versus placebo on recurrent VTE, major vascular events (recurrent VTE, myocardial infarction, stroke, and cardiovascular disease death) and bleeding, overall and within predefined subgroups. The primary analysis, for VTE, was by intention to treat using time-to-event data. Of 1224 patients, 193 had recurrent VTE over 30.4 months' median follow-up. Aspirin reduced recurrent VTE (7.5%/yr versus 5.1%/yr; hazard ratio [HR], 0.68; 95% confidence interval [CI], 0.51-0.90; P=0.008), including both deep-vein thrombosis (HR, 0.66; 95% CI, 0.47-0.92; P=0.01) and pulmonary embolism (HR, 0.66; 95% CI, 0.41-1.06; P=0.08). Aspirin reduced major vascular events (8.7%/yr versus 5.7%/yr; HR, 0.66; 95% CI, 0.50-0.86; P=0.002). The major bleeding rate was low (0.4%/yr for placebo and 0.5%/yr for aspirin). After adjustment for treatment adherence, recurrent VTE was reduced by 42% (HR, 0.58; 95% CI, 0.40-0.85; P=0.005). Prespecified subgroup analyses indicate similar relative, but larger absolute, risk reductions in men and older patients. Aspirin after anticoagulant treatment reduces the overall risk of recurrence by more than a third in a broad cross-section of patients with a first unprovoked VTE, without significantly increasing the risk of bleeding. www.anzctr.org.au. Unique identifier: ACTRN12611000684921.

Coping strategies as mediators of the effect of the START (strategies for RelaTives) intervention on psychological morbidity for family carers of people with dementia in a randomised controlled trial

BackgroundFamily carers of people with dementia frequently become depressed or anxious. In observational studies, more emotion-focused and less dysfunctional coping predict fewer psychological symptoms, but no randomised controlled trial (RCT) has directly investigated emotion-focused coping as mediator of effectiveness of a successful psychological intervention. We hypothesised that emotion-focused coping would mediate the START psychological intervention׳s effects in an RCT. We tested whether mediated effects were moderated by severity of baseline symptoms. Methods260 family carers from NHS dementia services were randomised to START (manualised coping skills intervention), or treatment-as-usual (TAU). Blinded raters administered the Hospital Anxiety and Depression Scale (HADS-T) and Brief COPE inventory at baseline, 4 and 8 months. HADS-T improved in the intervention group when compared to TAU at all levels of psychological distress. We tested whether coping was a mediator and for moderated mediation, and (post-hoc) subgroup treatment effects on coping. ResultsData were available for 187 carers (71.9%) for the mediation analysis. The reduced HADS-T score in the intervention group was mediated by increased emotion-focused coping only among carers with higher (16+) baseline HADS-T scores (mediated effect=−0.63 [−1.11, −0.15]; proportion of overall effect=33% [3%, 64%]). LimitationsWe did not measure plausible psychosocial treatment mechanisms other than coping. ConclusionsSTART benefited family carers both in preventing and treating psychological morbidity, through different mechanisms of action. The most psychologically distressed carers increased their emotion-focused coping and did not decrease their dysfunctional coping, while others benefited but not through this mechanism.

Predictors of chronic obstructive pulmonary disease exacerbation reduction in response to daily azithromycin therapy.

Daily azithromycin decreases acute exacerbations of chronic obstructive pulmonary disease (AECOPD), but long-term side effects are unknown. To identify the types of exacerbations most likely to be reduced and clinical subgroups most likely to benefit from azithromycin, 250 mg daily, added to usual care. Enrollment criteria included irreversible airflow limitation and AECOPD requiring corticosteroids, emergency department visit, or hospitalization in the prior year or use of supplemental oxygen. Recurrent events and cumulative incidence analyses compared treatment received for AECOPD by randomization group, stratified by subgroups of interest. Cox proportional hazards models estimated treatment effects in subgroups adjusted for age, sex, smoking status, FEV1% predicted, concomitant COPD medications, and oxygen use. Azithromycin was most effective in reducing AECOPD requiring both antibiotic and steroid treatment (n = 1,113; cumulative incidence analysis, P = 0.0002; recurrent events analysis, P = 0.002). No difference in treatment response by sex (P = 0.75), presence of chronic bronchitis (P = 0.19), concomitant inhaled therapy (P = 0.29), or supplemental oxygen use (P = 0.23) was observed. Older age and milder Global Initiative for Chronic Obstructive Lung Disease stage were associated with better treatment response (P = 0.02 and 0.04, respectively). A significant interaction between treatment and current smoking was seen (P = 0.03) and azithromycin did not reduce exacerbations in current smokers (hazard ratio, 0.99; 95% confidence interval, 0.71-1.38; P = 0.95). Azithromycin is most effective in preventing AECOPD requiring both antibiotic and steroid treatment. Adjusting for confounders, we saw no difference in efficacy by sex, history of chronic bronchitis, oxygen use, or concomitant COPD therapy. Greater efficacy was seen in older patients and milder Global Initiative for Chronic Obstructive Lung Disease stages. We found little evidence of treatment effect among current smokers. Clinical trial registered with www.clinicaltrials.gov (NCT0011986 and NCT00325897).

Assessing the impact of propensity score estimation and implementation on covariate balance and confounding control within and across important subgroups in comparative effectiveness research.

Researchers are often interested in estimating treatment effects in subgroups controlling for confounding based on a propensity score (PS) estimated in the overall study population. To evaluate covariate balance and confounding control in sulfonylurea versus metformin initiators within subgroups defined by cardiovascular disease (CVD) history comparing an overall PS with subgroup-specific PSs implemented by 1:1 matching and stratification. We analyzed younger patients from a US insurance claims database and older patients from 2 Medicare (Humana Medicare Advantage, fee-for-service Medicare Parts A, B, and D) datasets. Confounders and risk factors for acute myocardial infarction were included in an overall PS and subgroup PSs with and without CVD. Covariate balance was assessed using the average standardized absolute mean difference (ASAMD). Compared with crude estimates, ASAMD across covariates was improved 70%-94% for stratification for Medicare cohorts and 44%-99% for the younger cohort, with minimal differences between overall and subgroup-specific PSs. With matching, 75%-99% balance improvement was achieved regardless of cohort and PS, but with smaller sample size. Hazard ratios within each CVD subgroup differed minimally among PS and cohorts. Both overall PSs and CVD subgroup-specific PSs achieved good balance on measured covariates when assessing the relative association of diabetes monotherapy with nonfatal myocardial infarction. PS matching generally led to better balance than stratification, but with smaller sample size. Our study is limited insofar as crude differences were minimal, suggesting that the new user, active comparator design identified patients with some equipoise between treatments.

Abstract T P119: Effective Pre-Planned Center Selection to Optimize Sample Heterogeneity in the Interdisciplinary Comprehensive Arm Rehabilitation Evaluation (ICARE) Multi-site Trial

For phase III RCTs, sample heterogeneity is useful for both generalizability of findings and providing insight into treatment effects for specific subgroups. Prior studies in stroke rehabilitation have rarely explored differences in intervention effects between racial and ethnic subgroups across participating sites. We examined participant characteristics across centers, with the hypothesis that strategic use of a multi-center structure across 3 distinct urban geographical areas (Atlanta, GA, Los Angeles, CA and Washington, DC) would generate a sample diverse enough to explore differences in treatment effects by racial and ethnic subgroups Methods: The ICARE Stroke Initiative is a randomized multi-center clinical trial designed to compare the effectiveness of the Accelerated Skill Acquisition Program (ASAP) to an equivalent dose of usual and customary outpatient occupational therapy (DEUCC) and a monitoring only usual therapy group (UCC). Demographics, stroke characteristics and cognitive outcomes collected at baseline for randomized participants (N = 361) were compared across the 3 centers using ANOVA or χ2 tests for continuous and categorical outcomes, respectively. Results: We found significant differences in race and ethnicity (p<0.001); the highest proportion of African-Americans came from the Atlanta and DC centers, and the highest proportion of Hispanic/Latinos came from the Los Angeles center. Additional unanticipated differences between centers in baseline characteristics include: age, referral source, stroke location, stroke severity as measured by the NIH Stroke Scale, Short Blessed Memory Test, DKEF’s verbal fluency sub-score of category switching, and pre-randomization hours of outpatient occupational therapy (p<0.05). Conclusions: ICARE’s strategic center selection resulted in a diverse and robust dataset, allowing for post hoc exploration of treatment effect differences by subgroup and for the intention-to-treat analysis, determination of generalizability of treatment effects across a racially and ethnically diverse population.

Long-term Follow-up of MRC Myeloma IX Trial: Survival Outcomes with Bisphosphonate and Thalidomide Treatment

Medical Research Council (MRC) Myeloma IX was a phase III trial evaluating bisphosphonate and thalidomide-based therapy for newly diagnosed multiple myeloma. Results were reported previously after a median follow-up of 3.7 years (current controlled trials number: ISRCTN68454111). Survival outcomes were reanalyzed after an extended follow-up (median, 5.9 years). At first randomization, patients (N = 1,970) were assigned to bisphosphonate (clodronic acid or zoledronic acid) and induction therapies [cyclophosphamide-vincristine-doxorubicin-dexamethasone (CVAD) or cyclophosphamide-thalidomide-dexamethasone (CTD) followed by high-dose therapy plus autologous stem cell transplantation for younger/fitter patients (intensive pathway), and melphalan-prednisone (MP) or attenuated CTD (CTDa) for older/less fit patients (nonintensive pathway)]. At second randomization, patients were assigned to thalidomide maintenance therapy or no maintenance. Interphase FISH (iFISH) was used to analyze cytogenics. Zoledronic acid significantly improved progression-free survival (PFS; HR, 0.89; P = 0.02) and overall survival (OS; HR, 0.86; P = 0.01) compared with clodronic acid. In the intensive pathway, CTD showed noninferior PFS and OS compared with CVAD, with a trend toward improved OS in patients with favorable cytogenics (P = 0.068). In the nonintensive pathway, CTDa significantly improved PFS (HR, 0.81; P = 0.007) compared with MP and there was an emergent survival benefit after 18 to 24 months. Thalidomide maintenance improved PFS (HR, 1.44; P < 0.0001) but not OS (HR, 0.96; P = 0.70), and was associated with shorter OS in patients with adverse cytogenics (P = 0.01). Long-term follow-up is essential to identify clinically meaningful treatment effects in myeloma subgroups based on cytogenetics.

Marker Sequential Test (MaST) design.

New targeted anticancer therapies often benefit only a subset of patients with a given cancer. Definitive evaluation of these agents may require phase III randomized clinical trial designs that integrate evaluation of the new treatment and the predictive ability of the biomarker that putatively determines the sensitive subset. We propose a new integrated biomarker design, the Marker Sequential Test (MaST) design, that allows sequential testing of the treatment effect in the biomarker subgroups and overall population while controlling the relevant type I error rates. After defining the testing and error framework for integrated biomarker designs, we review the commonly used approaches to integrated biomarker testing. We then present a general form of the MaST design and describe how it can be used to provide proper control of false-positive error rates for biomarker-positive and biomarker-negative subgroups. The operating characteristics of the MaST design are compared by analytical methods and simulations to the sequential subgroup-specific design that sequentially assesses the treatment effect in the biomarker subgroups. Practical aspects of MaST design implementation are discussed. The MaST design is shown to have higher power relative to the sequential subgroup-specific design in situations where the treatment effect is homogeneous across biomarker subgroups, while preserving the power for settings where treatment benefit is limited to biomarker-positive subgroup. For example, in the time-to-event setting considered with 30% biomarker-positive prevalence, the MaST design provides up to a 30% increase in power in the biomarker-positive and biomarker-negative subgroups when the treatment benefits all patients equally, while sustaining less than a 2% loss of power against alternatives where the benefit is limited to the biomarker-positive subgroup. The proposed design is appropriate for settings where it is reasonable to assume that the treatment will not be effective in the biomarker-negative patients unless it is effective in the biomarker-positive patients. The MaST trial design is a useful alternative to the sequential subgroup-specific design when it is important to consider the treatment effect in the biomarker-positive and biomarker-negative subgroups.

Indirect Estimation of the Comparative Treatment Effect in Pharmacogenomic Subgroups

Evidence of clinical utility is a key issue in translating pharmacogenomics into clinical practice. Appropriately designed randomized controlled trials generally provide the most robust evidence of the clinical utility, but often only data from a pharmacogenomic association study are available. This paper details a method for reframing the results of pharmacogenomic association studies in terms of the comparative treatment effect for a pharmacogenomic subgroup to provide greater insight into the likely clinical utility of a pharmacogenomic marker, its’ likely cost effectiveness, and the value of undertaking the further (often expensive) research required for translation into clinical practice. The method is based on the law of total probability, which relates marginal and conditional probability. It takes as inputs: the prevalence of the pharmacogenomic marker in the patient group of interest, prognostic effect of the pharmacogenomic marker based on observational association studies, and the unstratified comparative treatment effect based on one or more conventional randomized controlled trials. The critical assumption is that of exchangeability across the included studies. The method is demonstrated using a case study of cytochrome P450 (CYP) 2C19 genotype and the anti-platelet agent clopidogrel. Indirect subgroup analysis provided insight into relationship between the clinical utility of genotyping CYP2C19 and the risk ratio of cardiovascular outcomes between CYP2C19 genotypes for individuals using clopidogrel. In this case study the indirect and direct estimates of the treatment effect for the cytochrome P450 2C19 subgroups were similar. In general, however, indirect estimates are likely to have substantially greater risk of bias than an equivalent direct estimate.

A review of phase II trial designs for initial marker validation

Phase II clinical trials aim to identify promising experimental regimens for further testing in phase III trials. In this review article, we focus on phase II designs for initial predictive biomarker validation to determine if a drug should be developed for an unselected patient population or for a biomarker-defined patient subset only. Several prospective designs for biomarker-directed therapy have been proposed, differing primarily in the study population, or randomization scheme, or both. The design choice is driven by scientific rationale, marker prevalence, strength of preliminary evidence, assay performance, and turn-around times for marker assessment. The enrichment design is most appropriate when compelling preliminary evidence suggests treatment benefit in only certain marker-defined subgroups, the all-comers design is useful when preliminary evidence regarding treatment effects in marker subgroups is unclear, and adaptive designs have the most potential in the setting of multiple treatment options and multiple marker-defined subgroups. We recently proposed a 2-stage phase II design that has the option for direct assignment (i.e., stop randomization and assign all patients to the experimental arm in stage 2) based on interim analysis (IA) results. This design not only recognizes the need for randomization but also acknowledges the possibility of promising but inconclusive results after pre-planned IA. Simulation studies demonstrated that the direct assignment-option design has minimal power loss, marginal increase in type I error rates, and reasonable robustness to population shift effects. Systematic evaluation and implementation of these design strategies in the phase II setting are essential for accelerating the clinical validation of biomarker guided-therapy.

Meta-Analysis and Subgroups

Subgroup analysis is the process of comparing a treatment effect for two or more variants of an intervention-to ask, for example, if an intervention's impact is affected by the setting (school versus community), by the delivery agent (outside facilitator versus regular classroom teacher), by the quality of delivery, or if the long-term effect differs from the short-term effect. While large-scale studies often employ subgroup analyses, these analyses cannot generally be performed for small-scale studies, since these typically include a homogeneous population and only one variant of the intervention. This limitation can be bypassed by using meta-analysis. Meta-analysis allows the researcher to compare the treatment effect in different subgroups, even if these subgroups appear in separate studies. We discuss several statistical issues related to this procedure, including the selection of a statistical model and statistical power for the comparison. To illustrate these points, we use the example of a meta-analysis of obesity prevention.

Teplizumab treatment may improve C-peptide responses in participants with type 1 diabetes after the new-onset period: a randomised controlled trial

Type 1 diabetes results from a chronic autoimmune process continuing for years after presentation. We tested whether treatment with teplizumab (a Fc receptor non-binding anti-CD3 monoclonal antibody), after the new-onset period, affects the decline in C-peptide production in individuals with type 1 diabetes. In a randomised placebo-controlled trial we treated 58 participants with type 1 diabetes for 4-12months with teplizumab or placebo at four academic centres in the USA. A central randomisation centre used computer generated tables to allocate treatments. Investigators, patients, and caregivers were blinded to group assignment. The primary outcome was a comparison of C-peptide responses to a mixed meal after 1year. We explored modification of treatment effects in subgroups of patients. Thirty-four and 29 subjects were randomized to the drug and placebo treated groups, respectively. Thirty-one and 27, respectively, were analysed. Although the primary outcome analysis showed a 21.7% higher C-peptide response in the teplizumab-treated group (0.45 vs 0.371; difference, 0.059 [95% CI 0.006, 0.115] nmol/l) (p = 0.03), when corrected for baseline imbalances in HbA(1c) levels, the C-peptide levels in the teplizumab-treated group were 17.7% higher (0.44 vs 0.378; difference, 0.049 [95% CI 0, 0.108] nmol/l, p = 0.09). A greater proportion of placebo-treated participants lost detectable C-peptide responses at 12months (p = 0.03). The teplizumab group required less exogenous insulin (p < 0.001) but treatment differences in HbA(1c) levels were not observed. Teplizumab was well tolerated. A subgroup analysis showed that treatment benefits were larger in younger individuals and those with HbA(1c) <6.5% at entry. Clinical responders to teplizumab had an increase in circulating CD8 central memory cells 2months after enrolment compared with non-responders. This study suggests that deterioration in insulin secretion may be affected by immune therapy with teplizumab after the new-onset period but the magnitude of the effect is less than during the new-onset period. Our studies identify characteristics of patients most likely to respond to this immune therapy. ClinicalTrials.gov NCT00378508 This work was supported by grants 2007-502, 2007-1059 and 2006-351 from the JDRF and grants R01 DK057846, P30 DK20495, UL1 RR024139, UL1RR025780, UL1 RR024131 and UL1 RR024134 from the NIH.

Dexpramipexole effects on functional decline and survival in subjects with amyotrophic lateral sclerosis in a Phase II study: Subgroup analysis of demographic and clinical characteristics

Our objective was to explore treatment effects in patient subgroups using post hoc analyses of data from part 2 of the dexpramipexole Phase II study. Subjects with amyotrophic lateral sclerosis (ALS) received dexpramipexole 300 mg/day or 50 mg/day for 24 weeks. Treatment effects on the slope of the revised ALS Functional Rating Score (ALSFRS-R) and Combined Assessment of Function and Survival (CAFS) were evaluated in dichotomized subgroups: riluzole use, gender, site of symptom onset. Other subgroups were dichotomized using median baseline values for age, ALSFRS-R, slow vital capacity, symptom duration, diagnostic delay, and progression rate. Results showed that there was a 21% reduction in ALSFRS-R decline favoring the 300-mg vs. 50-mg arm (p = 0.177); mean CAFS ranking was significantly higher in the 300-mg vs. 50-mg arm (52.4 vs. 41.1; p = 0.046). Trends were recapitulated in virtually all subgroups. Generally, ALSFRS-R decline was reduced and CAFS rankings were higher in the 300-mg vs. 50-mg arm across subgroups. CAFS rankings were significantly higher in the 300-mg vs. 50-mg arm among subjects with ALSFRS-R scores ≤35, symptom duration <18.7 months, or progression rate ≥ 0.7 points/month (p < 0.03). In conclusion, the observed benefit of 300- vs. 50-mg dexpramipexole on functional decline and survival was generally consistent among subjects regardless of baseline characteristics.

On Bayesian methods of exploring qualitative interactions for targeted treatment

Providing personalized treatments designed to maximize benefits and minimizing harms is of tremendous current medical interest. One problem in this area is the evaluation of the interaction between the treatment and other predictor variables. Treatment effects in subgroups having the same direction but different magnitudes are called quantitative interactions, whereas those having opposite directions in subgroups are called qualitative interactions (QIs). Identifying QIs is challenging because they are rare and usually unknown among many potential biomarkers. Meanwhile, subgroup analysis reduces the power of hypothesis testing and multiple subgroup analyses inflate the type I error rate. We propose a new Bayesian approach to search for QI in a multiple regression setting with adaptive decision rules. We consider various regression models for the outcome. We illustrate this method in two examples of phase III clinical trials. The algorithm is straightforward and easy to implement using existing software packages. We provide a sample code in Appendix A.

Heterogeneity of treatment effects.

Heterogeneity of treatment effects.

Effect of Predictive Performance of a Biomarker for the Sample Size of Targeted Designs for Randomized Clinical Trials

Targeted designs based on the use of predictive biomarkers for patient enrollment have been used to increase the study efficiency. We consider the problem of efficiency of targeted design when the targeted subgroup is defined by a predictive biomarker or classifier. Here we incorporate the predictive performance of a biomarker or classifier to predict a responsive subgroup in the sample size evaluation for targeted design. Predictive performance metrics such as PPV and NPV of a predictive biomarker can usually be best estimated from preclinical studies, such as cell line panel screening. In this article, we focus on sample size calculations for clinical trial studies with time-to-event endpoint. Different assumptions on the treatment and control effects for the subgroups of patients are assumed. Patients’ accrual rate and losses to follow-up are incorporated in the sample size calculation. Simulations are used to check the performance of the sample size formulas. Also, the efficiency of a targeted versus untargeted design is evaluated using cohort size ratio and screened patient ratio. In these studies, the efficiency depends primarily on the prevalence of the subgroup targeted for trial enrollment, the treatment and control effects in subgroups defined by the biomarkers, PPV and NPV.

Telemedicine in heart failure: Pre-specified and exploratory subgroup analyses from the TIM-HF trial

BackgroundMeta-analyses have suggested that remote telemedical management (RTM) positively affects clinical outcomes in chronic HF patients. The results of two recent randomised RTM trials do not corroborate these results. We aim to report prospectively defined and exploratory subgroup analyses for the TIM-HF trial and to identify a patient profile that could potentially benefit from RTM for further investigation in randomised clinical trials. MethodsIn TIM-HF, 710 stable chronic HF patients, in NYHA class II or III with a history of HF decompensation within 2years previously or a LVEF≤25% were randomly assigned (1:1) to RTM or usual care. The primary outcome was total death and secondary outcomes included days lost due to death or HF hospitalisation and a composite of cardiovascular death and HF hospitalisation. Twelve subgroups were prospectively defined and patient profiling was investigated for the subgroup with a prior history of HF decompensation, an LVEF≥25% and a PHQ-9 score<10. ResultsThe subgroup treatment effects were significant for total mortality for the PHQ-9 subgroup only (p for interaction<0.027). For the outcome ‘number of days lost due to hospitalisation for HF or death’, the subgroup treatment effects were significant (p for interaction<0.05) for patients with a prior HF decompensation or an ICD implant or a PHQ score of <10 and for the patient-profiling subgroup. ConclusionsTelemedicine management may not be appropriate for all HF patients. Future research needs to investigate which HF population may benefit from this intervention.