Kunst N, Alarid-Escudero F, Paltiel A, Wang SY.
Value in Health. 2019;22(10):1102-1110.
The 21-gene assay Oncotype DX (21-GA) shows promise as a guide in deciding when to initiate adjuvant chemotherapy in women with hormone receptor–positive early-stage breast cancer. Nevertheless, its routine use remains controversial, owing to insufficient evidence of its clinical utility and cost-effectiveness. Accordingly, we aim to quantify the value of conducting further research to reduce decision uncertainty in the use of the 21-GA.
Using value of information methods, we first generated probability distributions of survival and costs for decision making with and without the 21-GA alongside traditional risk prediction. These served as the input to a comparison of 3 alternative study designs: a retrospective observational study to update risk classification from the 21-GA, a prospective observational study to estimate prevalence of chemotherapy use, and a randomized controlled trial (RCT) of the 21-GA predictive value.
We found that current evidence strongly supports the use of the 21-GA in intermediate- and high-risk women. Further research should focus on low-risk women, among whom the cost-effectiveness findings remained equivocal. For this population, we identified a high value of reducing uncertainty in the 21-GA use for all proposed research studies. The RCT had the greatest potential to efficiently reduce the likelihood of choosing a suboptimal strategy, providing a value between $162 million and $1.1 billion at willingness-to-pay thresholds of $150 000 to $200 000/quality-adjusted life years.
Future research to inform 21-GA decision making is of high value. The RCT of the 21-GA predictive value has the greatest potential to efficiently reduce decision uncertainty around 21-GA use in women with low-risk early-stage breast cancer.
Doupe P, Faghmous J, Basu S.
Value in Health. 2019;22(7):808-815.
This article explains how to optimize Bayesian D-efficient discrete choice experiment (DCE) designs for the estimation of quality-adjusted life year (QALY) tariffs that are unconfounded by respondents' time preferences.
The calculation of Bayesian D-errors is explained for DCE designs that allow for the disentanglement of respondents' time and health-state preferences. Time preferences are modelled via an exponential, hyperbolic, or power discount function and the performance of the proposed DCE designs is compared with that of several conventional DCE designs that do not take nonlinear time preferences into account.
Based on the achieved D-error, asymptotic standard error, and estimated sample size to obtain statistically significant estimates of the discount rate parameters, the proposed designs outperform the conventional DCE designs.
We recommend that applied researchers use appropriately optimized DCE designs for the estimation of QALY tariffs that are corrected for time preferences. The TPC-QALY software package that accompanies this article makes the recommended designs easily accessible for health-state valuation researchers.
van Egdom L, Oemrawsingh A, Verweij L, Lingsma H, Koppert L, Verhoef C, Klazinga N, Hazelzet J.
Value in Health. 2019;22(10):1197-1226.
Patient-reported outcome measures (PROMs) are increasingly being used to improve care delivery and are becoming part of routine clinical practice.
This systematic review aims to give an overview of PROM administration methods and their facilitators and barriers in breast cancer clinical practice.
A systematic literature search was conducted in Embase, MEDLINE, PsycINFO, Cochrane Central, CINAHL, and Web of Science for potentially relevant articles from study inception to November 2017. Reference lists of screened reviews were also checked. After inclusion of relevant articles, data were extracted and appraised by 2 investigators.
A total of 2311 articles were screened, of which 34 eligible articles were ultimately included. Method and frequency of PROM collection varied between studies. The majority of studies described a promising effect of PROM collection on patients (adherence, symptom distress, quality of life, acceptability, and satisfaction), providers (willingness to comply, clinical decision making, symptom management), and care process or system outcomes (referrals, patient-provider communication, hospital visits). A limited number of facilitators and barriers were identified, primarily of a technical and behavioral nature.
Although interpreting the impact of PROM collection in breast cancer care is challenging owing to considerations of synergistic (multicomponent) interventions and generalizability issues, this review found that systematic PROM collection has a promising impact on patients, providers, and care processes/ systems. Further standardization and reporting on method and frequency of PROM collection might help increase the effectiveness of PROM interventions and is warranted to enhance their overall impact.