The comparative effectiveness of decision aids in diverse populations with early stage prostate cancer: a study protocol for a cluster-randomized controlled trial in the NCI Community Oncology Research Program (NCORP), Alliance A191402CD

The symbolic two-step method applied to cancer care delivery research: Safeguarding against designing an underpowered cluster randomized trial with a continuous outcome by accounting for the imprecision in the within- and between-center variation

BACKGROUND

Knowing the predictive factors of the variation in a center-level continuous outcome of interest is valuable in the design and analysis of parallel-arm cluster randomized trials. The symbolic two-step method for sample size planning that we present incorporates this knowledge while simultaneously accounting for patient-level characteristics. Our approach is illustrated through application to cluster randomized trials in cancer care delivery research. The required number of centers (clusters) depends on the between- and within-center variance; the within-center variance is a function of estimates obtained by regressing the log within-center variance on predictive factors. Obtaining accurate estimates of the components needed to characterize the within-center variation is challenging.

METHODS

Using our previously derived sample size formula, our objective in the current research is to directly account for the imprecision in these estimates, using a Bayesian approach, to safeguard against designing an underpowered study when using the symbolic two-step method. Using estimates of the required components, including the number of centers that contribute to those estimates, we make formal allowance for the imprecision in these estimates on which a sample size will be based.

RESULTS

The mean of the distribution for power is consistently smaller than the single point estimate that the sample size formula yields. The reduction in power is more pronounced in the presence of increased uncertainty about the estimates with the reduction becoming more attenuated with increased numbers of centers that contribute to the estimates.

CONCLUSIONS

Accounting for imprecision in the estimates of the components required for sample size estimation using the symbolic two-step method in the design of a cluster randomized trial yields conservative estimates of power.

Lessons learned from conducting the first cancer care delivery trial in the Alliance for Clinical Trials in Oncology (Alliance A191402CD)

INTRODUCTION

Testing healthcare delivery interventions in rigorous clinical trials is a critical step in improving patient care, but conducting multisite randomized clinical trials to test the effect of care delivery interventions has unique challenges and requires foresight and planning.

METHODS

We conducted the first care delivery trial (A191402CD) in the Alliance for Clinical Trials in Oncology, a National Cancer Institute Community Oncology Research Program research base, which tested the effectiveness of two different decision aids for supporting shared decision-making about prostate cancer treatment. Our experience illustrates the kind of challenges that confront care delivery researchers as they seek to test interventions to improve the experiences of patients.

RESULTS

Lessons learned include the following: cluster-randomized designs introduce complexity; workflow disruption can discourage site participation; evidence-based methods may not always be sufficient.

CONCLUSION

We conclude with the following recommendations: assessing feasibility requires special rigor; relationships and interpersonal dynamics must be leveraged. Our experiences may inform future care delivery research.

The Impact of Within-Consultation and Preconsultation Decision Aids for Localized Prostate Cancer on Patient Knowledge: Results of a Patient-Level Randomized Trial

OBJECTIVE

To evaluate the role of timing (either before or during initial consultation) on the effectiveness of decision aids (DAs) to support shared-decision-making in a minority-enriched sample of patients with localized prostate cancer using a patient-level randomized controlled trial design.

METHODS

We conducted a 3-arm, patient-level-randomized trial in urology and radiation oncology practices in Ohio, South Dakota, and Alaska, testing the effect of preconsultation and within-consultation DAs on patient knowledge elements deemed essential to make treatment decisions about localized prostate cancer, all measured immediately following the initial urology consultation using a 12-item Prostate Cancer Treatment Questionnaire (score range 0 [no questions correct] to 1 [all questions correct]), compared to usual care (no DAs).

RESULTS

Between 2017 and 2018, 103 patients-including 16 Black/African American and 17 American Indian or Alaska Native men-were enrolled and randomly assigned to receive usual care (n = 33) or usual care and a DA before (n = 37) or during (n = 33) the consultation. After adjusting for baseline characteristics, there were no statistically significant proportional score differences in patient knowledge between the preconsultation DA arm (0.06 knowledge change, 95% CI -0.02 to 0.12, P = .1) or the within-consultation DA arm (0.04 knowledge change, 95% CI -0.03 to 0.11, P = .3) and usual care.

CONCLUSION

In this trial oversampling minority men with localized prostate cancer, DAs presented at different times relative to the specialist consultation showed no improvement in patient knowledge above usual care.

Novel pictograms to improve pharmacist understanding of the number needed to treat (NNT)

INTRODUCTION

Number needed to treat (NNT) is a clinically useful "yardstick" used to gauge the efficacy of therapeutic interventions. The objective of this project was to develop and pilot a series of pictograms and assess their impact on pharmacist understanding of the NNT.

METHODS

Three decision aids containing NNT pictograms were developed following a preliminary literature review and three focus groups with current Australian-registered pharmacists and pharmacist interns. Pharmacists then tested the pictograms in a research pilot in clinical encounters until (1) ≥ 3 sessions had occurred or (2) a two-week period had elapsed from commencement. Knowledge assessment was administered both pre- and post-pilot. Transcription and inductive thematic analysis were applied to focus group data. Descriptive statistics, Wilcoxon signed rank, and McNemar's tests were used to analyse the pilot data.

RESULTS

Six core themes regarding NNT decision aid development were identified with >80% consensus across three focus groups (N = 11). Comparison of the pre-post measures (n = 10) showed an increase in median scores after use of NNT decision aids, correlating to a moderate Cohen classified effect size (d = 0.54). Wilcoxon matched pairs test demonstrated a statistically insignificant influence of NNT pictograms on the knowledge assessment survey (P > .05).

CONCLUSIONS

While the NNT is not a new concept, its incorporation as part of pictograms for health practitioner enrichment is novel. This pilot study suggests that utilizing decision aids with NNT pictograms as counselling adjuncts appears promising in the realm of enhancing pharmacists' understanding of the NNT.

Successes and lessons learned in database development for national multi-site cancer care delivery research trials: the Alliance for Clinical Trials in Oncology experience

INTRODUCTION

Alliance for Clinical Trials in Oncology (Alliance) coordinated trials utilize Medidata Rave® (Rave) as the primary clinical data capture system. A growing number of innovative and complex cancer care delivery research (CCDR) trials are being conducted within the Alliance with the aims of studying and improving cancer-related care. Because these trials encompass patients, providers, practices, and their interactions, a defining characteristic of CCDR trials is multilevel data collection in pragmatic settings. Consequently, CCDR trials necessitated innovative strategies for database development, centralized data management, and data monitoring in the presence of these real-world multilevel relationships. Having real trial experience in working with community and academic centers, and having recently implemented five CCDR trials in Rave, we are committed to sharing our strategies and lessons learned in implementing such pragmatic trials in oncology.

METHODS

Five Alliance CCDR trials are used to describe our approach to analyzing the database development needs and the novel strategies applied to overcome the unanticipated challenges we encountered. The strategies applied are organized into 3 categories: multilevel (clinic, clinic stakeholder, patient) enrollment, multilevel quantitative and qualitative data capture, including nontraditional data capture mechanisms being applied, and multilevel data monitoring.

RESULTS

A notable lesson learned in each category was (1) to seek long-term solutions when developing the functionality to push patient and non-patient enrollments to their respective Rave study database that affords flexibility if new participant types are later added; (2) to be open to different data collection modalities, particularly if such modalities remove barriers to participation, recognizing that additional resources are needed to develop the infrastructure to exchange data between that modality and Rave; and (3) to facilitate multilevel data monitoring, orient site coordinators to the their trial's multiple study databases, each corresponding to a level in the hierarchy, and remind them to establish the link between patient and non-patient participants in the site-facing NCI web-based enrollment system.

CONCLUSION

Although the challenges due to multilevel data collection in pragmatic settings were surmountable, our shared experience can inform and foster collaborations to collectively build on our past successes and improve on our past failures to address the gaps.

Decision aids for localized prostate cancer in diverse minority men: Primary outcome results from a multicenter cancer care delivery trial (Alliance A191402CD)

BACKGROUND

Decision aids (DAs) can improve knowledge for prostate cancer treatment. However, the relative effects of DAs delivered within the clinical encounter and in more diverse patient populations are unknown. A multicenter cluster randomized controlled trial with a 2×2 factorial design was performed to test the effectiveness of within-visit and previsit DAs for localized prostate cancer, and minority men were oversampled.

METHODS

The interventions were delivered in urology practices affiliated with the NCI Community Oncology Research Program Alliance Research Base. The primary outcome was prostate cancer knowledge (percent correct on a 12-item measure) assessed immediately after a urology consultation.

RESULTS

Four sites administered the previsit DA (39 patients), 4 sites administered the within-visit DA (44 patients), 3 sites administered both previsit and within-visit DAs (25 patients), and 4 sites provided usual care (50 patients). The median percent correct in prostate cancer knowledge, based on the postvisit knowledge assessment after the intervention delivery, was as follows: 75% for the pre+within-visit DA study arm, 67% for the previsit DA only arm, 58% for the within-visit DA only arm, and 58% for the usual-care arm. Neither the previsit DA nor the within-visit DA had a significant impact on patient knowledge of prostate cancer treatments at the prespecified 2.5% significance level (P = .132 and P = .977, respectively).

CONCLUSIONS

DAs for localized prostate cancer treatment provided at 2 different points in the care continuum in a trial that oversampled minority men did not confer measurable gains in prostate cancer knowledge.

Decision Aids for Shared Decision-making in Uro-oncology: A Systematic Review

CONTEXT

Decision aids (DAs) aim to support patients in the process of shared decision-making for complex treatment decisions. To improve patient-centered care in uro-oncology, it is essential to evaluate the availability and quality of existing DAs.

OBJECTIVE

To assess the quality of existing DAs for patients across the most prevalent uro-oncological entities.

EVIDENCE ACQUISITION

This study was conducted in accordance with the Preferred Reporting Items for Systematic Review and Meta-analyses (PRISMA) guidelines. A systematic literature search (MedLine, Cochrane Library, Web of Science Core Collection, and CCMed) was conducted to identify DAs for treatment decisions for patients with prostate, renal, or bladder cancer. All studies reporting on the development or evaluation of DAs were included. The DAs were examined based on the International Patient Decision Aid Standards (IPDAS) and the evaluation studies were compared in accordance with Standards for Universal reporting of a patient Decision Aid Evaluations (SUNDAE).

EVIDENCE SYNTHESIS

The literature search identified 1995 potentially relevant publications. Thirty-two studies reporting on 25 DAs met the inclusion criteria. Twenty-two DAs address prostate cancer, two renal tumor, and one bladder cancer. In the majority of DAs (n = 20), patients can enter individual data. A few (n = 6) DAs allow for personalization using a risk-adapted presentation of treatment options. The percentage of IPDAS criteria met in DAs ranged between 50% and 100% (median 87.5%), and the studies' adherence to the SUNDAE checklist was between 62% and 96% (median 86.6%). Evaluation studies suggest that interventions are likely efficacious. However, a preliminary meta-analysis revealed no significant difference between "DA" and "usual care" for decisional conflict or decisional regret.

CONCLUSIONS

This review highlights that a number of well-developed DAs exist in urology. However, there is a need for specific instruments targeting kidney and bladder cancer. Personalization of tools and adherence to international standards of DAs should be further improved.

PATIENT SUMMARY

The majority of uro-oncological decision aids target prostate cancer, whereas fewer address kidney or bladder cancer. The quality of the existing instruments is high, but can be increased further to better address specific needs of individual patients.