Treatment Effects In Presence Research Articles

Estimation of treatment effect in presence of noncompliance and competing risks: a simulation study

A randomized controlled trial is commonly designed to assess the treatment effect in survival studies, in which patients are randomly assigned to the standard or the experimental treatment group. Upon disease progression, patients who have been randomized to standard treatment are allowed to switch to the experimental treatment. Treatment switching in a randomized controlled trial refers to a situation in which patients switch from their randomized treatment to another treatment. Often, the switchis from the control group to the experimental treatment. In this case, the treatment effect estimate is adjusted using either convenient naive methods such as intention-to-treat, per-protocol or advanced methods such as rank preserving structural failure time (RPSFT) models. In previous simulation studies performed so far, there was only one possible outcome for patients. However, in oncology in particular, multiple outcomes are potentially possible. These outcomes are called competing risks. This aspect has not been considered in previous studies when determining the effect of a treatment in the presence of noncompliance. This study aimed to extend the RPSFT method using a two-dimensional G-estimation in the presence of competing risks. The RPSFT method was extended for two events, the event of interest and the competing event. For this purpose, the RPSFT method was applied based on the cause-specific hazard approach, the result of which is compared to the naive methods used in simulation studies. The results show that the proposed method has a good performance compared to other methods.

Predicting personalised absolute treatment effects in individual participant data meta-analysis: An introduction to splines.

Modelling non-linear associations between an outcome and continuous patient characteristics, whilst investigating heterogeneous treatment effects, is one of the opportunities offered by individual participant data meta-analysis (IPD-MA). Splines offer great flexibility, but guidance is lacking. To introduce modelling of nonlinear associations using restricted cubic splines (RCS), natural B-splines, P-splines, and smoothing splines in IPD-MA to estimate absolute treatment effects. We describe the pooling of spline-based models using pointwise and multivariate meta-analysis (two-stage methods) and one-stage generalised additive mixed effects models (GAMMs). We illustrate their performance on three IPD-MA scenarios of five studies each: one where only the associations differ across studies, one where only the ranges of the effect modifier differ and one where both differ. We also evaluated the approaches in an empirical example, modelling the risk of fever and/or ear pain in children with acute otitis media conditional on age. In the first scenario, all pooling methods showed similar results. In the second and third scenario, pointwise meta-analysis was flexible but showed non-smooth results and wide confidence intervals; multivariate meta-analysis failed to converge with RCS, but was efficient with natural B-splines. GAMMs produced smooth pooled regression curves in all settings. In the empirical example, results were similar to the second and third scenario, except for multivariate meta-analysis with RCS, which now converged. We provide guidance on the use of splines in IPD-MA, to capture heterogeneous treatment effects in presence of non-linear associations, thereby facilitating estimation of absolute treatment effects to enhance personalized healthcare.

Estimation of treatment effect in presence of noncompliance with early or late switching: a simulation study

To assess the effect of treatment in survival studies, a randomized controlled trial (RCTs) is usually designed. Due to disease progression or other safety reasons, patients in the standard group may be allowed to switch to the experimental treatment. In such cases, estimation of the treatment effect is inevitably performed using naive methods such as intention-to-treat (ITT), per-protocol (PP), or more advanced methods such as the rank-preserving structural failure time (RPSFT) models or iterative parameter estimation (IPE). In some trials, people who progress early might be more likely to switch, and in other trials, people who progress late might be more likely to switch – depending on the characteristics of the disease and the drug being examined. So, this study simulated a new range of realistic scenarios with regard to patients’ prognosis and investigated the performance of the adjusted methods in the early and late switching with respect to the median of the survival time.

Centrally Reduced Diffusion Sign for Differentiation between Treatment-Related Lesions and Glioma Progression: A Validation Study.

Differentiating between treatment-related lesions and tumor progression remains one of the greatest dilemmas in neuro-oncology. Diffusion MR imaging characteristics may provide useful information to help make this distinction. The aim of the study was to assess the diagnostic accuracy of the centrally reduced diffusion sign for differentiation of treatment-related lesions and true tumor progression in patients with suspected glioma recurrence. The images of 231 patients who underwent an operation for suspected glioma recurrence were reviewed. Patients with susceptibility artifacts or without central necrosis were excluded. The final diagnosis was established according to histopathology reports. Two neuroradiologists classified the diffusion patterns on preoperative MR imaging as the following: 1) reduced diffusion in the solid component only, 2) reduced diffusion mainly in the solid component, 3) no reduced diffusion, 4) reduced diffusion mainly in the central necrosis, and 5) reduced diffusion in the central necrosis only. Diagnostic accuracy metrics and the area under the receiver operating characteristic curve were estimated for the diffusion patterns. One hundred three patients were included (22 with treatment-related lesions and 81 with tumor progression). The diagnostic accuracy results for the centrally reduced diffusion pattern as a predictor of treatment-related lesions ("mainly central" and "exclusively central" patterns versus all other patterns) were as follows: 64% sensitivity (95% CI, 41%-83%), 84% specificity (95% CI, 74%-91%), 52% positive predictive value (95% CI, 37%-66%), and 89% negative predictive value (95% CI, 83%-94%). The centrally reduced diffusion sign is associated with the presence of treatment effect. The probability of a histologic diagnosis of a treatment-related lesion is low (11%) in the absence of centrally reduced diffusion.

Presence of Histopathological Treatment Effects at Resection of Recurrent Glioblastoma: Incidence and Effect on Outcome.

Resection may be appropriate for select patients with recurrent glioblastoma. The incidence of histopathological findings related to prior treatment and their prognostic implications are incompletely characterized. To quantify the incidence and survival outcomes associated with treatment effect at resection of recurrent glioblastoma (GBM). Patients who underwent resection for recurrent GBM were retrospectively reviewed, and pathology, treatment history, and survival data were collected. Treatment effect was defined as any component of treatment-related changes on pathology. In total, 110 patients underwent 146 reoperations. Median age at first reoperation was 57.2 yr and overall survival from reoperation was 10.8 mo. Treatment effect of any kind was noted in 81 of 146 reoperations (55%). Increased treatment effect was observed closer to radiotherapy; by quartile of time from radiotherapy, the rates of treatment effect were 77.8%, 55.6%, 40.7%, and 44.4% (P=.028). Treatment effect was associated with earlier reoperation (8.9 vs 13.8 mo after radiotherapy, P=.003), and the presence of treatment effect did not impact survival from primary surgery (25.4 vs 24.3 mo, P=.084). Patients treated with bevacizumab prior to reoperation were less likely to have treatment effect (20% vs 65%, P<.001). Histopathological treatment-related changes are evident in a majority of patients undergoing resection for recurrent glioblastoma. There was no association of treatment effect with overall survival from primary surgery.

NIMG-51. THE CENTRALLY RESTRICTED DIFFUSION SIGN FOR DIFFERENTIATION BETWEEN TREATMENT-RELATED LESIONS AND TUMOR PROGRESSION IN GLIOMA PATIENTS: A VALIDATION STUDY

Abstract BACKGROUND The aim of the study was to compare the diagnostic accuracy of different diffusion patterns for differentiation between treatment-related lesions and true tumor progression in patients with suspected glioma recurrence. METHODS A retrospective analysis of a prospective cohort was conducted. The images of 240 consecutive patients who underwent surgery for suspected glioma recurrence were reviewed for potential inclusion. Exclusion criteria were lack of a ring-enhancing lesion and presence of susceptibility artifact. Final diagnosis was established upon review of histopathology reports. Lesions showing treatment-related changes and less than 25% of viable tumor were considered treatment-related lesions. More than 25% of viable tumor was considered recurrent tumor. A neuroradiologist, blinded to the diagnosis, evaluated the diffusion patterns on preoperative MRI. ROC curve analysis was performed. RESULTS One hundred and ten patients were included (26 with treatment-related lesions and 84 with tumor progression). Of 110, 35 showed no reduced diffusion. Fifty patients had reduced diffusion in the solid lesion component (84%, recurrent tumor and 16%, treatment-related lesions). Twenty-five patients showed reduced diffusion within the central necrosis (48%, recurrent tumor and 52%, treatment-related lesions). Most cases with reduced diffusion in the central necrotic region showed mixed pathology with concurrent treatment effect and viable tumor. The AUC for the combined diffusion pattern (reduced diffusion in the solid lesion component vs in the necrotic region) was 0.68 (95%CI=0.55–0.81). The AUC for the traditional diffusion approach (reduced diffusion in the solid lesion component vs no reduced diffusion) was 0.59 (95%CI=0.49–070). No significant differences were found in AUC (p=0.3). CONCLUSION Although the existence of centrally reduced diffusion seems to be associated with the presence of treatment effect, it does not significantly increase the diagnostic accuracy of the traditional diffusion evaluation approach. This is most likely related to the high incidence of concurrent recurrent tumor and treatment effect.

AN EMOTION REGULATION THERAPY FOR LATER-LIFE PAIN: EVIDENCE OF EARLY TREATMENT EFFECTS

Chronic pain (CP) is a common, morbid, and costly disorder in older adults. Guidelines encourage clinicians to employ non-pharmacologic therapies for its management, but current psychological interventions (e.g., CBT for pain) have modest treatment benefits and their effects are largely unknown in older cognitively impaired adults. We developed PATH-Pain, an emotion regulation therapy focused on reducing negative emotions and augmenting positive emotions. PATH-Pain is appropriate for use by older adults with CP, negative emotions, and a wide range of cognitive functioning. Treatment consists of 8 weekly individual sessions followed by 4 monthly booster sessions. One hundred older adults (ages 60+) with CP (≥ 3 months) and at least mild-to-moderate levels of negative emotions (per the Positive and Negative Affect Schedule) were randomized to receive PATH-Pain versus Usual Care (UC). Cognitive screening revealed that 44 participants were cognitively intact (Montreal Cognitive Assessment (MoCA) score ≥26), while 56 evidenced mild-to-moderate cognitive impairment (MoCA=16-25). Participants completed follow-ups at 5 (n=89) and 10 weeks (n=84), while 24-week assessments are ongoing. Examination of the treatment × time interaction in a repeated-measures mixed model indicate the presence of treatment effects. PATH-Pain (vs. UC) participants experienced significant reductions in pain intensity (p<0.044) and pain-related disability (p<0.003). Reductions in pain-related disability score were more pronounced among cognitively impaired individuals. The PATH-Pain group also demonstrated significant reductions in emotional suppression (p<0.019) and depression (p<0.009) scores. These results suggest that PATH-Pain is an effective treatment for the management of pain in cognitively intact and cognitively impaired older adults.

Consistent estimation of polychotomous treatment effects with selection-bias and unobserved heterogeneity using panel data correlated random coefficients model

We estimate multiple treatment effects in presence of selection-bias and response heterogeneity, using panel data. A control function was added to a fixed-effects based correlated random coefficients model. Selection model to create the control function was contrasted between multinomial logit and multinomial probit. For the multinomial logit model, parametric and semi-parametric bias correction techniques, as proposed in Lee (Econometrica 51(2):507–512, 1983), Dubin and McFadden (Econometrica 52(2):345–362, 1984) and Dahl (Econometrica 70(6):2367–2420, 2002) respectively, were implemented. We find that controlling time-varying endogeneity, allowing response heterogeneity, the type of bias correction method and the choice of the selection model, each had significant impact on the estimated treatment effects. Using the case of biologic DMARDs, we show that in the presence of heterogeneity and multiple treatments, the specification of the latent index model should be carefully chosen along with selection bias correction techniques appropriate to the choice of the latent index model. These issues have an important impact on policy. Under one set of assumptions, we may accept a formulary expansion policy on biologic DMARDs to be cost-neutral, while rejecting the same policy as not cost-saving under another set of assumptions.

Predictors of Disease Recurrence and Survival in Esophageal Adenocarcinomas With Complete Response to Neoadjuvant Therapy.

Complete response to neoadjuvant therapy, determined by pathologic examination of the resection specimen (pCR), is associated with a favorable outcome in esophageal adenocarcinomas (EAC), but there is significant heterogeneity in survival reported within this group. Our aim was to determine predictors of disease recurrence (DR) and survival in EAC patients with pCR to neoadjuvant therapy. A total of 93 EAC patients with pCR to neoadjuvant therapy were identified, and a predetermined set of clinicopathologic variables was examined, including patient age, sex, tumor location, pretreatment tumor size, endoscopic ultrasound T and N stage, histologic tumor type, and grade in pretreatment biopsies. The esophagectomy specimens were evaluated for the extent of sampling of the tumor bed, depth of treatment-related changes, presence of treatment effect in lymph nodes, and the total number of lymph nodes examined. Complete histologic examination of the tumor bed was the most significant predictor of favorable outcome for both DR (hazard ratio [HR]=0.42; 95% confidence interval [CI]: 0.21-0.82; P=0.011) and disease-specific mortality (HR=0.40; 95% CI: 0.22-0.70; P<0.01). The presence of a high-grade adenocarcinoma component in pretreatment biopsies (HR=2.19; 95% CI: 1.22-3.94; P<0.01) was associated with a higher disease-specific mortality, and involvement of the gastroesophageal junction (HR=2.37; 95% CI: 1.11-5.06; P=0.026) was associated with a higher rate of DR. Heterogeneity in outcomes for EAC patients with pCR to therapy can be explained by adequacy of histologic examination of the tumor bed, high tumor grade, and involvement of the gastroesophageal junction.

Choosing Appropriate Estimands in Clinical Trials.

Lack of adherence to study protocol and missing data are often unavoidable in clinical trials, and both increase the need to differentiate between the ideal treatment effect if the medication is taken as directed and the treatment effect in presence of the actual adherence pattern. In this regard, estimands have become the focus of attention. An estimand is simply that which is being estimated. In the context of treatment benefit, an estimand may address either efficacy or effectiveness aspects. Defining the estimand of interest is an essential step to take before deciding on trial design and primary analysis. The choice of estimand has consequences for various other factors to be considered during any clinical trial's planning phase. This study presents a process chart including all aspects to consider during planning. After deciding on the primary estimand, the trial design should be specified, followed by the primary analysis. Both should appropriately address the chosen estimand. Finally, sensitivity analyses should be taken into account. Provided are suggestions for all the planning steps involved, especially on choosing between efficacy and effectiveness, and relevant examples from clinical practice to illustrate them. It is recommended that one bear in mind the process chart during planning of any clinical trial and give reasonable justification for each decision in the study protocol.

A Novel Methodology to Estimate the Treatment Effect in Presence of Highly Variable Placebo Response

One of the main reasons for the inefficiency of multicenter randomized clinical trials (RCTs) in depression is the excessively high level of placebo response. The aim of this work was to propose a novel methodology to analyze RCTs based on the assumption that centers with high placebo response are less informative than the other centers for estimating the 'true' treatment effect (TE). A linear mixed-effect modeling approach for repeated measures (MMRM) was used as a reference approach. The new method for estimating TE was based on a nonlinear longitudinal modeling of clinical scores (NLMMRM). NLMMRM estimates TE by associating a weighting factor to the data collected in each center. The weight was defined by the posterior probability of detecting a clinically relevant difference between active treatment and placebo at that center. Data from five RCTs in depression were used to compare the performance of MMRM with NLMMRM. The results of the analyses showed an average improvement of ~15% in the TE estimated with NLMMRM when the center effect was included in the analyses. Opposite results were observed with MMRM: TE estimate was reduced by ~4% when the center effect was considered as covariate in the analysis. The novel NLMMRM approach provides a tool for controlling the confounding effect of high placebo response, to increase signal detection and to provide a more reliable estimate of the 'true' TE by controlling false negative results associated with excessively high placebo response.

Estimation of Treatment and Carryover Effects in Optimal Cross-Over Designs for Clinical Trials

A particular multi-period cross-over design useful in trials where observations naturally are correlated and carryover effect may not die after one period—such as thorough QT, trials on diet, asthma, and others—is shown to be useful for estimation in three practical cases. The cases are: the variance balanced estimation of direct and carryover treatment effects in presence of higher-order carryover and correlated errors using ordinary least squares method; estimation of the said treatment effects under scattered missing observations; and the interim estimation of the same for trials with early stopping rules. We compare treatment effect estimates and their variances with those given in the literature for the higher-order carryover model. We also give a numerical example demonstrating estimation in all three cases.

Use of Two-Stage Test Statistic in the Two-Period Crossover Trials

For two-period crossover trials where the residual carryover can only exist in the presence of treatment effect, Willan (1988, Biometrics 44, 211-218) recommended use of the maximum test statistic that chooses the analysis with the larger test statistic corresponding to the parallel analysis and the crossover analysis. We construct two alternative two-stage test procedures, based on Grizzle's approach, that maintain the actual type I error rate at the desirable level. The power, accuracy, and precision of the analysis based on the modified two-stage procedures are compared to those based on the parallel analysis, crossover analysis, and the maximum test statistic.

Evaluating treatment effects in single-subject behavioral experiments using quality-control charts

Quality-control charts can be particularly useful in identifying treatment effects and patterns of behaviors in single-subject behavior-analytic experiments that cannot be determined by visual inspection of their graphs. Using an example from the behavior analysis literature the quality-control charts identified the presence of treatment effects across phases as well as the presence of trends within and between phases. The ease of their calculations suggest use of them by behavior analysts whenever the effects of particular interventions are questionable.

Incomplete Repeated Measures Data Analysis in the Presence of Treatment Effects

Abstract This article illustrates an analysis strategy for repeated measures data where some of the measurements are missing from the subjects on one or more occasions, with a special application to data arising from repeated measurement designs when some observations are missing after the first treatment period. Using all available data, “almost” maximum likelihood estimators for the parameters of interest are obtained under the assumption of a multivariate normal distribution of the data. Inference procedures for these parameters in small samples from popular two-treatment designs are discussed.

Incomplete Repeated Measures Data Analysis in the Presence of Treatment Effects

Incomplete Repeated Measures Data Analysis in the Presence of Treatment Effects