Comparative Effectiveness and Durability of Biologics in Clinical Practice: Month 12 Outcomes from the International, Observational Psoriasis Study of Health Outcomes (PSoHO).

INTRODUCTION: Given the chronic nature of psoriasis (PsO), more studies are needed that directly compare the effectiveness of different biologics over long observation periods. This study compares the effectiveness and durability through 12 months of anti-interleukin (IL)-17A biologics relative to other approved biologics in patients with moderate-to-severe psoriasis in a real-world setting. METHODS: The Psoriasis Study of Health Outcomes (PSoHO) is an ongoing 3-year, prospective, non-interventional cohort study of 1981 adults with chronic moderate-to-severe plaque psoriasis initiating or switching to a new biologic. The study compares the effectiveness of anti-IL-17A biologics with other approved biologics and provides pairwise comparisons of seven individual biologics versus ixekizumab. The primary outcome was defined as the proportion of patients who had at least a 90% improvement in Psoriasis Area and Severity Index score (PASI90) and/or a score of 0 or 1 in static Physician Global Assessment (sPGA). Secondary objective comparisons included the proportion of patients who achieved PASI90, PASI100, a Dermatology Life Quality Index (DLQI) score of 0 or 1, and three different measures of durability of treatment response. Unadjusted response rates are presented alongside the primary analysis, which uses frequentist model averaging (FMA) to evaluate the adjusted comparative effectiveness. RESULTS: Compared to the other biologics cohort, the anti-IL-17A cohort had a higher response rate (68.0% vs. 65.1%) and significantly higher odds of achieving the primary outcome at month 12. The two cohorts had similar response rates for PASI100 (40.5% and 37.1%) and PASI90 (53.9% and 51.7%) at month 12, with no significant differences between the cohorts in the adjusted analyses. At month 12, the response rates across the individual biologics were 53.5-72.6% for the primary outcome, 27.6-48.3% for PASI100, and 41.7-61.4% for PASI90. CONCLUSIONS: These results show the comparative effectiveness of biologics at 6 and 12 months in the real-world setting.

Aligning Estimators With Estimands in Clinical Trials: Putting the ICH E9(R1) Guidelines Into Practice.

The draft ICH E9(R1) addendum stipulates that an estimator should align with its associated estimand and yield an estimate that facilitates reliable interpretations. The addendum further stipulates that assumptions should be justifiable and plausible, and that the extent of assumptions is an important consideration for whether an estimate will be robust because assumptions are often unverifiable. The draft addendum specifies 5 strategies for dealing with intercurrent events. The intent of this paper is to provide conceptual considerations and technical details for various estimators that align with these strategies. We include focus on how the nature and extent of assumptions influences the potential robustness of the various estimators. The content reflects the knowledge, experience, and opinions of the Drug Information Association's Scientific Working Group on Missing Data. This group includes experienced statisticians from across industry and academia, primarily in the US and European Union.

A structured approach to choosing estimands and estimators in longitudinal clinical trials.

An important evolution in the missing data arena has been the recognition of need for clarity in objectives. The objectives of primary focus in clinical trials can often be categorized as assessing efficacy or effectiveness. The present investigation illustrated a structured framework for choosing estimands and estimators when testing investigational drugs to treat the symptoms of chronic illnesses. Key issues were discussed and illustrated using a reanalysis of the confirmatory trials from a new drug application in depression. The primary analysis used a likelihood-based approach to assess efficacy: mean change to the planned endpoint of the trial assuming patients stayed on drug. Secondarily, effectiveness was assessed using a multiple imputation approach. The imputation model-derived solely from the placebo group-was used to impute missing values for both the drug and placebo groups. Therefore, this so-called placebo multiple imputation (a.k.a. controlled imputation) approach assumed patients had reduced benefit from the drug after discontinuing it. Results from the example data provided clear evidence of efficacy for the experimental drug and characterized its effectiveness. Data after discontinuation of study medication were not required for these analyses. Given the idiosyncratic nature of drug development, no estimand or approach is universally appropriate. However, the general practice of pairing efficacy and effectiveness estimands may often be useful in understanding the overall risks and benefits of a drug. Controlled imputation approaches, such as placebo multiple imputation, can be a flexible and transparent framework for formulating primary analyses of effectiveness estimands and sensitivity analyses for efficacy estimands.

Predictors of remission with placebo using an integrated study database from patients with major depressive disorder.

OBJECTIVE: To identify predictors of remission with placebo treatment in double-blind randomized controlled trials (RCTs) in major depressive disorder (MDD). METHOD: A total of 1017 placebo-treated patients with baseline Hamilton Depression rating scale (HAMD) total ≥15 from eight duloxetine RCTs were included. Remission was defined as endpoint (7-8 weeks) HAMD total ≤7. Data were randomly split into training data (N = 813, 80%) for model selection and test data (N = 204, 20%) for validation. Logistic regression and classification and regression tree (CART) methods were used to identify predictors of remission. Predictive accuracy of models was assessed by Receiver Operator Characteristic (ROC) curves. RESULTS: Baseline predictors for remission with placebo consistently identified with the logistic regression and CART analysis were less severe depressive symptoms (based on HAMD core symptoms), younger age, less anxiety (based on HAMD anxiety/somatization), and shorter current MDD episode duration. Associated cut-off values from the CART method characterized patient groups according to their remission likelihood. However, the predictive accuracy was modest for both methods with areas under the ROC curve of 0.6-0.65 based on test data. CONCLUSION: The derived models, although of limited value for predicting remission in individual patients, may be useful for adjusting for placebo effects in clinical trials.

In search of optimal lithium levels and olanzapine doses in the long-term treatment of bipolar I disorder. A post-hoc analysis of the maintenance study by Tohen et al. 2005.

PURPOSE: The aim of this study was to investigate whether lower lithium levels (LoLi) or olanzapine doses (LoOL) are risk factors for future mood episodes in patients with bipolar I disorder. METHODS: A post-hoc analysis of the olanzapine-lithium-maintenance study [31] was performed using proportional hazards Cox regression models and marginal structural models (MSMs), adjusting for non-random assignments of dose during treatment. RESULTS: The LoLi group (<0.6 mmol/L) had a significantly increased risk of manic/mixed (hazard ratio [HR]=1.96, p=0.042), but not depressive (HR=2.11, p=0.272) episodes, compared to the combined medium (0.6-0.79 mmol/L) and high lithium level (≥0.8 mmol/L) groups. There was no significant difference in risk between the two higher lithium level groups (0.6-0.79 mmol/L; ≥0.8 mmol/L) for new manic/mixed (HR=0.96, p=0.893) or depressive (HR=0.95, p=0.922) episodes. The LoOL group (<10mg/day) showed a significantly increased risk of depressive (HR=2.24, p=0.025) episodes compared to the higher olanzapine (HiOL) dose group (HiOL: 10-20 mg/day), while there was no statistically significant difference in risk for manic/mixed episodes between the two groups (HR=0.94, p=0.895). CONCLUSION: Lithium levels≥0.6 mmol/L and olanzapine doses≥10mg/day may be necessary for optimal protection against manic/mixed or depressive episodes, respectively in patients with bipolar I disorder.

Predictors of risk for relapse in patients with schizophrenia or schizoaffective disorder during olanzapine drug therapy.

PURPOSE: To evaluate the relationship of dose decrease, symptom worsening, and baseline covariates on subsequent relapse during olanzapine treatment in patients with schizophrenia or schizoaffective disorder. METHODS: In two 28-week, randomized, double-blind clinical trials, a Cox proportional hazards model was used to determine potential correlates of relapse (defined as > or =20% worsening on PANSS total and CGI-Severity 3) among patients (N=271) who responded to 8 weeks of olanzapine treatment (10-20mg/day). Variables examined included: demographics, illness characteristics, baseline symptoms, symptom change, dose, adverse events, and functioning. RESULTS: Patients with a lower last dose relative to the preceding visit interval were 4 times more likely to relapse during that visit interval than other patients (p<.001). A similar finding was observed for a decrease in interval modal dose, although this variable was more predictive of relapse in the visit interval immediately following dose decrease (p=.027). In a subgroup analysis by gender, there was a significantly greater incidence of relapse in men with a dose decrease, whereas a dose decrease in women did not correlate with relapse. Relapse was also correlated with the emergence or worsening of a psychiatric adverse event during the same (p<.001) and preceding (p=.007) visit intervals, and with increased rating scale measures of psychopathology. The occurrence of a non-psychiatric adverse event was not associated with relapse. CONCLUSION: Dose decrease is a significant predictor of relapse in male but not female patients. Psychiatric adverse events also predicted relapse. Patients should be periodically reassessed to determine the need for maintenance treatment with appropriate dose.