Analyzing patient‐reported outcome data when completion differs between arms in open‐label trials: an application of principal stratification

2019 ◽  
Vol 28 (10) ◽  
pp. 1386-1394 ◽  
Author(s):  
Jessica K. Roydhouse ◽  
Roee Gutman ◽  
Vishal Bhatnagar ◽  
Paul G. Kluetz ◽  
Rajeshwari Sridhara ◽  
...  
Keyword(s):  
Patient Reported Outcome ◽  
Outcome Data ◽  
Principal Stratification ◽  
Open Label ◽  
Patient Reported

PatientConcept App � an innovative tool to improve therapy adherence and to implement risk management plans. (Preprint)

2018 ◽  
Author(s):  
Michael Lang ◽  
Martin Mayr ◽  
Stefan Ringbauer ◽  
Lukas Cepek
Keyword(s):  
Risk Management ◽  
Disease Management ◽  
Chronically Ill ◽  
Patient Reported Outcome ◽  
Outcome Data ◽  
Daily Routine ◽  
Software Application ◽  
Patient Reported ◽  
Management Plans ◽  
Chronically Ill Patients

UNSTRUCTURED Background: Adherence constitutes a great challenge for disease management, particularly when treating chronically ill patients facing an extensive, complex and long-term therapy. Earlier studies emphasize the relevance of adherence for improving therapy benefits. Besides the positive impact of increased patient support, the use of mobile health applications has gained importance in disease management. Objective: We aimed to develop a software application providing innovative features to simplify the contact between patients and treating physicians in order to overcome adherence barriers, to implement risk management plans and to collect patient reported outcome data. Methods: A novel software application ensuring data security was developed. Various innovative modules have been implemented, enabling bidirectional communication between treating physicians and patients, supporting therapy monitoring and management and allowing the collection of large sets of anonymous patient data. Results: The PatientConcept app is freely available for download and is tested since 2016, with more than 1800 generated patient IDs and 279 patients documenting health data according to risk management plans online in 2017. The impact on adherence issues is currently tested in larger patient populations. Conclusion: This innovative app provides a feasible and cost-optimized possibility to intensify and simplify the communication between patients and their treating physicians across indications, thus promising an exceptional benefit to both. It may not only support chronically ill patients in managing their daily life and improving adherence, but can also facilitate the implementation of risk management plans through automated monitoring, thus supporting physicians in their daily routine. Furthermore, patient reported outcome data can be collected. Importantly, a secure ID-associated data management ensures patient anonymity complying with highest data safety standards.

Impact of Blinding on Patient-Reported Outcome Differences Between Treatment Arms in Cancer Randomized Controlled Trials

2021 ◽  
Author(s):  
Fabio Efficace ◽  
David Cella ◽  
Neil K Aaronson ◽  
Melanie Calvert ◽  
Francesco Cottone ◽  
...  
Keyword(s):  
Randomized Controlled Trials ◽  
Experimental Treatment ◽  
Patient Reported Outcome ◽  
Controlled Trials ◽  
Open Label ◽  
Multivariable Logistic Regression Model ◽  
Randomized Controlled ◽  
Patient Reported ◽  
Independent Variable ◽  
Outcome Differences

Abstract Some concerns have been raised about potential bias in patient-reported outcome (PRO) results from open-label cancer randomized controlled trials (RCTs). We investigated if open-label trials favor the experimental treatment over the standard treatment more frequently than blinded trials. We also examined if the effect of blinding differs for distal vs more proximal PROs. We assessed 538 RCTs with a PRO endpoint conducted in the most prevalent cancers, of which 366 (68.0%) were open-label, 148 (27.5%) were blinded, and 24 (4.5%) were categorized as unclear. In our multivariable logistic regression model, we did not observe a statistically significant association of the independent variable treatment concealment (blinded vs open-label) on the dependent variable measuring the proportion of trials favoring the experimental treatment (adjusted odds ratio = 1.19, 95% confidence interval = 0.79 to 1.79; 2-sided P = .40). This was also the case when comparing distal and proximal PROs. Our findings provide novel evidence-based data that support the validity of PRO results from open-label cancer RCTs.

Health-related quality-of-life (HRQoL) analysis from a randomized phase II trial of androgen signaling inhibitors with or without androgen deprivation therapy (ADT) for castration-sensitive prostate cancer: LACOG 0415.

2021 ◽  
Vol 39 (6_suppl) ◽  
pp. 64-64
Author(s):  
Andrey Soares ◽  
Diogo Assed Bastos ◽  
Fabio A. B. Schutz ◽  
Eduardo Cronemberger ◽  
Murilo Luz ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Locally Advanced ◽  
Patient Reported Outcome ◽  
Abiraterone Acetate ◽  
Outcome Data ◽  
Rank Test ◽  
Emotional Wellbeing ◽  
Patient Reported ◽  
Related Quality

64 Background: LACOG0415 is a 3-arm randomized trial evaluating ADT with abiraterone acetate plus prednisone (ADT+AAP), apalutamide alone (APA) or apalutamide with AAP (APA+AAP) for patients with locally-advanced, high-risk biochemical recurrence or metastatic castration-sensitive prostate cancer (ASCO 2020). In this trial, ADT+AAP and APA+AAP achieved the primary endpoint of percentage of patients with PSA ≤ 0.2 ng/mL at week 25. Apalutamide alone showed a high PSA decline > 50% rate, but did not achieve the pre-specified PSA threshold. Here we report patient-reported outcome data using Functional Assessment of Cancer Therapy-Prostate (FACT-P). Methods: HRQoL was measured in the overall population using the FACT-P questionnaire, comprising 5 subscales: physical wellbeing (PWB), functional wellbeing (FWB), emotional wellbeing (EWB), social/family wellbeing (SFWB), and prostate cancer subscale (PCS). Scores for each patient were measured at baseline and every four weeks until week 25. Questionnaire completion was defined as ≥ 1 question answered at an assessment time point. Analysis of HRQoL change from baseline and deterioration included only patients with baseline and ≥ 1 postbaseline score. Differences greater than 10-points in FACT-P total score and differences greater than 3-points in PWB, FWB, EWB, SFWB, and PCS scores were considered clinically significant. The time-to-event endpoint was estimated by Kaplan-Meier method and compared by stratified log-rank test. Results: 128 patients were included in LACOG0415 trial and 122 of them completed the HRQoL assessments (ranging from 95.3% at baseline to 79.7% at week 25). FACT-P and all subscales scores were similar for all three arms at baseline. There were no meaningful differences in FACT-P scores at baseline and at week 25 between the 3 arms. The subscales scores also showed no statistically differences at baseline and at week 25. Time to FACT-P deterioration did not show any statistically difference between three arms ( P=0.3371). Conclusions: ADT free alternatives with APA alone or APA+AAP did not show meaningful differences in HRQoL in patients with advanced castration-sensitive prostate cancer compared to ADT+AAP. The short follow-up period limited the ability to explore differences in HRQoL after 25 weeks. Larger studies with longer follow-up are needed to further evaluate HRQoL with ADT-free strategies. Clinical trial information: NCT02867020. [Table: see text]

Using generalized estimating equations and extensions in randomized trials with missing longitudinal patient reported outcome data

2018 ◽  
Vol 27 (9) ◽  
pp. 2125-2131 ◽  
Author(s):  
Melanie L. Bell ◽  
Nicholas J. Horton ◽  
Haryana M. Dhillon ◽  
Victoria J. Bray ◽  
Janette Vardy
Keyword(s):  
Generalized Estimating Equations ◽  
Randomized Trials ◽  
Estimating Equations ◽  
Patient Reported Outcome ◽  
Outcome Data ◽  
Patient Reported ◽  
Generalized Estimating

scholarly journals Obtaining Patient Reported Outcome Data in the Era of Electronic Medical Records

2018 ◽  
Vol 24 (3) ◽  
pp. S267-S268
Author(s):  
Lauren E. Brister ◽  
Leland Metheny ◽  
Linda K. Baer ◽  
Molly Gallogly
Keyword(s):  
Electronic Medical Records ◽  
Medical Records ◽  
Patient Reported Outcome ◽  
Outcome Data ◽  
Patient Reported

Patient-Reported Outcome Data

2019 ◽  
pp. 249-267
Author(s):  
Robert O. Morgan ◽  
Kavita R. Sail ◽  
Laura E. Witte
Keyword(s):  
Patient Reported Outcome ◽  
Outcome Data ◽  
Patient Reported
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