The Use of a Variable Representing Compliance Improves Accuracy of Estimation of the Effect of Treatment Allocation Regardless of Discontinuation in Trials with Incomplete Follow-up

Abstract–In Clinical Trials, not all randomized patients follow the course of treatment they are allocated to. The potential impact of such deviations is increasingly recognized, and it has been one of the reasons for a redefinition of the targets of estimation (“Estimands”) in the ICH E9 draft Addendum. Among others, the effect of treatment assignment, regardless of the adherence, appears an Estimand of practical interest, in line with the intention-to-treat principle. This study aims at evaluating the performance of different estimation techniques in trials with incomplete post-discontinuation follow-up when a “treatment-policy” strategy is implemented. To achieve that, we have (i) modeled and visualized as directed acyclic diagram a reasonable data-generating model; (ii) investigated which set of variables allows identification and estimation of such effect; (iii) simulated 10,000 trials in Major Depressive Disorder, with varying real treatment effects, proportions of patients discontinuing the treatment, and incomplete follow-up. Our results suggest that, at least in a “Missing at Random” setting, all studied estimation methods increase their performance when a variable representing compliance is used. This effect is more pronounced the higher the proportion of post-discontinuation follow-up is

Preferences about Future Alzheimer’s Disease Treatments Elicited through an Online Survey Using the Threshold Technique

Background: Treatments aiming at slowing down the progression of Alzheimer’s disease (AD) may soon become available. However, information about the risks that people are willing to accept in order to delay the progression of the disease is limited.Objective: To determine the trade-offs that individuals are willing to make between the benefits and risks of hypothetical treatments for AD, and the extent to which these trade-offs depend on individuals’ characteristics and beliefs about medicines.Design: Online, cross-sectional survey study.Setting: Population in the UK. Public link to the survey available at the websites of Alzheimer’s Research UK and Join Dementia Research.Participants: Everyone self-reported ≥18 years old was eligible to participate. A total of 4384 people entered the survey and 3658 completed it.Measurements: The maximum acceptable risks (MARs) of participants for moderate and severe adverse events in exchange for a 2-year delay in disease progression. The risks were expressed on ordinal scales, from &lt;10% to ≥50%, above a pre-existing risk of 30% for moderate adverse events and 10% for severe adverse events. We obtained the population median MARs using log-normal survival models and quantified the effects of individuals’ characteristics and beliefs about medicines in terms of acceleration factors.Results: For the moderate adverse events, 26% of the participants had a MAR ≥50%, followed by 25% of the participants with a MAR of 10 to &lt;20%, giving an estimated median MAR of 25.4% (95% confidence interval [CI] 24.5 to 26.3). For the severe adverse events, 43% of the participants had a MAR &lt;10%, followed by 25% of the participants with a MAR of 10 to &lt;20%, resulting in an estimated median MAR of 12.1% (95%CI 11.6 to 12.5). Factors that were associated with the individuals’ MARs for one or both adverse events were age, gender, educational level, living alone, and beliefs about medicines. Whether or not individuals were living with memory problems or had experience as a caregiver had no effect on the MARs for any of the adverse events.Conclusion: Trade-offs between benefits and risks of AD treatments are heterogeneous and influenced by individuals’ characteristics and beliefs about medicines. This heterogeneity should be acknowledged during the medicinal product decision-making in order to fulfil the needs of the various subpopulations.</p

The association of financial difficulties with clinical outcomes in cancer patients: secondary analysis of 16 academic prospective clinical trials conducted in Italy

Background: Cancer may cause financial difficulties, but its impact in countries with public health systems is unknown. We evaluated the association of financial difficulties with clinical outcomes of cancer patients enrolled in academic clinical trials performed within the Italian public health system. Patients and methods: Data were pooled from 16 prospective multicentre trials in lung, breast or ovarian cancer, using the EORTC quality of life (QOL) C30 questionnaire. Question 28 scores financial difficulties related to disease or treatment in four categories from 'not at all' to 'very much'. We defined financial burden (FB) as any financial difficulty reported at baseline questionnaire, and financial toxicity (FT) as score worsening in a subsequent questionnaire. We investigated (i) the association of FB with clinical outcomes (survival, global QOL response [questions 29/30] and severe toxicity), and (ii) the association of FT with survival. Multivariable analyses were performed using logistic regression models or the Cox model adjusting for trial, gender, age, region and period of enrolment, baseline global QOL and, where appropriate, FB and global QOL response. Results are reported as odds ratio (OR) or hazard ratio (HR) with 95% confidence intervals (CI). Results: At baseline 26% of the 3670 study patients reported FB, significantly correlated with worse baseline global QOL. FB was not associated with risks of death (HR 0.94, 95% CI 0.85-1.04, P = 0.23) and severe toxicity (OR 0.90, 95% CI 0.76-1.06, P = 0.19) but was predictive of a higher chance of worse global QOL response (OR 1.35, 95% CI 1.08-1.70, P = 0.009). During treatment, 2735 (74.5%) patients filled in subsequent questionnaires and 616 (22.5%) developed FT that was significantly associated with an increased risk of death (HR 1.20, 95% CI 1.05-1.37, P = 0.007). Several sensitivity analyses confirmed these findings. Conclusion: Even in a public health system, financial difficulties are associated with relevant cancer patients outcomes like QOL and survival

Cross-sectional study to develop and describe psychometric characteristics of a patient-reported instrument (PROFFIT) for measuring financial toxicity of cancer within a public healthcare system

Objectives To measure and explain financial toxicity (FT) of cancer in Italy, where a public healthcare system exists and patients with cancer are not expected (or only marginally) to pay out-of-pocket for healthcare. Setting Ten clinical oncological centres, distributed across Italian macroregions (North, Centre, South and Islands), including hospitals, university hospitals and national research institutes. Participants From 8 October 2019 to 11 December 2019, 184 patients, aged 18 or more, who were receiving or had received within the previous 3 months active anticancer treatment were enrolled, 108 (59%) females and 76 (41%) males. Intervention A 30-item prefinal questionnaire, previously developed within the qualitative tasks of the project, was administered, either electronically (n=115) or by paper sheet (n=69). Primary and secondary outcome measures According to the protocol and the International Society for Pharmacoeconomics and Outcomes Research methodology, the final questionnaire was developed by mean of explanatory factor analysis and tested for reliability, internal consistency (Cronbach's α test and item-total correlation) and stability of measurements over time (test-retest reliability by intraclass correlation coefficient and weighted Cohen's kappa coefficient). Results After exploratory factor analysis, a score measuring FT (FT score) was identified, made by seven items dealing with outcomes of FT. The Cronbach's alpha coefficient for the FT score was 0.87 and the item-total correlation coefficients ranged from 0.53 to 0.74. Further, nine single items representing possible determinants of FT were also retained in the final instrument. Test-retest analysis revealed a good internal validity of the FT score and of the 16 items retained in the final questionnaire. Conclusions The Patient-Reported Outcome for Fighting FInancial Toxicity (PROFFIT) instrument consists of 16 items and is the first reported instrument to assess FT of cancer developed in a country with a fully public healthcare system. Trial registration number NCT03473379

Hamilton scale and MADRS are interchangeable in meta-analyses but can disagree at trial level

Background and Objective: Major depressive disorder is a multidimensional disease, in which demonstrating the efficacy of treatments is difficult. The Hamilton Rating Scale for Depression (HRSD) and the Montgomery–Asberg Depression Rating Scale (MADRS) cover different domains but are used interchangeably as primary measures of the outcome in trials and—with standardized measures—in meta-analyses. We aimed at understanding (i) whether the choice of the outcome measurement tool can influence the outcome of a trial, and if so, (ii) whether one systematically outperforms the other, and (iii) whether using standardized measures of the effect in meta-analysis is justified. Methods: Short-term randomized trials in patients with major depressive disorder that used both the scales were systematically searched and the results were collected. To quantify the differences in the results—both in terms of the standardized mean difference (SMD) and odds ratio (OR) for response—and their range, data were analyzed and plotted with the Bland–Altman method. Results: 161 comparisons from 80 studies were included, involving a total of 18,189 patients. Neither of the two scales appears systematically more sensitive to the treatment effect than the other in terms of SMDs (P-value = 0.06, 95% CI −0.044 to 0.001) or ORs (P-value = 0.15, 95% CI −0.25 to 0.04). However, the variability of differences between the HRSD and MADRS largely depends on the number of patients included in the comparison. Conclusion: No systematic differences between the two scales were found supporting the use of standardized measures in meta-analyses. However, the same trial may give very different results with either scale, especially in small trials. Further research is needed to understand the causes of this variability

Beyond "Intent-to-treat" and "Per protocol": Improving assessment of treatment effects in clinical trials through the specification of an estimand

Contains fulltext : 225485.pdf (Publisher’s version ) (Open Access)There is a key problem in randomised clinical trials as outcomes can be distorted due to informative post-randomisation events. This is inadequately addressed by the use of traditional intention-to-treat or per protocol analysis sets and often either ignored or wrongly labelled as missing data. As a consequence, the treatment effects of interest in a clinical trial are not well defined and their estimates might be misinterpreted. The estimand framework should help all those planning, conducting and analysing clinical trials as well as those interpreting the results to better define, estimate and understand the treatment effects of interest. This framework is described in the addendum to ICH E9 and addresses precisely this problem. It is relevant for regulatory drug trials and academic-run trials, as well as for trials of nonpharmacological interventions

The opportunity of patient-journey studies for academic clinical research in oncology

A wave of new treatments and treatment combinations are becoming available for solid tumours. Trials performed to obtain registration establish a positive benefit-risk but unavoidably leave many questions unanswered on place-in-therapy and the relative efficacy of different treatment sequences. Such limitations create problems in terms of strength of treatment guidelines and reimbursement (in countries where a public payer exists). Data on new drugs arriving during the last 10 years for the treatment of hepatocellular carcinoma and renal cancer are reported as an example of how the fortunate condition of having new effective treatments may translate into uncertainty regarding the optimal treatment plan. We suggest that academic research should react to such limitations and propose a model of patient-journey study (PJS), where patients are followed from the initial diagnosis across subsequent lines of treatment. A PJS master protocol might include at each node of clinical decision either the possibility of choosing treatment according to guidelines (generating prospective real-world evidence) or the possibility to randomise where uncertainty exists (generating comparative effectiveness data). PJS protocols might be adaptively modified every time a new drug arrives on the market. Overall, methodologically sound analyses of PJS will produce knowledge on the efficacy and the effectiveness of different treatment pathways and might significantly optimise treatment of patients in clinical practice. PJS would represent a jump from a few snapshots (trials performed to get regulatory approval) to a full movie (evidence on the relative value of treatment pathways)

PNS114 IMPROVING THE TRANSPARENCY OF MARKETING AUTHORISATION DECISIONS: TOWARDS A FRAMEWORK FOR MANAGING UNCERTAINTIES

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