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Personalizing Medical Treatment Decisions: Integrating Meta-analytic Treatment Comparisons with Patient-Specific Risks and Preferences.

ABSTRACT: Background. Network meta-analyses (NMAs) that compare treatments for a given condition allow physicians to identify which treatments have higher or lower probabilities of reducing the risks of disease complications or increasing the risks of treatment side effects. Translating these data into personalized treatment plans requires integration of NMA data with patient-specific pretreatment risk estimates and preferences regarding treatment objectives and acceptable risks. Methods. We introduce a modeling framework to integrate data probabilistically from NMAs with data on individualized patient risk estimates for disease outcomes, treatment preferences (such as willingness to incur greater side effects for increased life expectancy), and risk preferences. We illustrate the modeling framework by creating personalized plans for antipsychotic drug treatment and evaluating their effectiveness and cost-effectiveness. Results. Compared with treating all patients with the drug that yields the greatest quality-adjusted life-years (QALYs) on average (amisulpride), personalizing the selection of antipsychotic drugs for schizophrenia patients over the next 5 years would be expected to yield 0.33 QALYs (95% credible interval [crI]: 0.30-0.37) per patient at an incremental cost of $4849/QALY gained (95% crI: dominant-$12,357), versus 0.29 and 0.04 QALYs per patient when accounting for only risks or preferences, respectively, but not both. Limitations. The analysis uses a linear, additive utility function to reflect patient treatment preferences and does not consider potential variations in patient time discounting. Conclusions. Our modeling framework rigorously computes what physicians normally have to do mentally. By integrating 3 key components of personalized medicine-evidence on efficacy, patient risks, and patient preferences-the modeling framework can provide personalized treatment decisions to improve patient health outcomes.

SUBMITTER: Weyant C

PROVIDER: S-EPMC6895439 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature

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Personalizing Medical Treatment Decisions: Integrating Meta-analytic Treatment Comparisons with Patient-Specific Risks and Preferences.

Weyant Christopher C Brandeau Margaret L ML Basu Sanjay S

Medical decision making : an international journal of the Society for Medical Decision Making 20191109 8

<b>Background.</b> Network meta-analyses (NMAs) that compare treatments for a given condition allow physicians to identify which treatments have higher or lower probabilities of reducing the risks of disease complications or increasing the risks of treatment side effects. Translating these data into personalized treatment plans requires integration of NMA data with patient-specific pretreatment risk estimates and preferences regarding treatment objectives and acceptable risks. <b>Methods.</b> We ...[more]

PMID: 31707910

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Project description:BackgroundPublic health care payer organizations face increasing pressures to make transparent and sustainable coverage decisions about ever more expensive prescription drugs, suggesting a need for public engagement in coverage decisions. However, little is known about countries' approaches to integrating public preferences in existing funding decisions. The aim of this study was to describe how Belgium and New Zealand used deliberative processes to engage the public and to identify lessons learned from these countries' approaches.MethodsTo describe two countries' deliberative processes, we first reviewed key country policy documents and then conducted semi-structured interviews with five leaders of the processes from Belgium and New Zealand. We assessed each country's rationales for and approaches to engaging the public in pharmaceutical coverage decisions and identified lessons learned. We used qualitative content analysis of the interviews to describe key themes and subthemes.ResultsIn both countries, the national public payer organization initiated and led the process of integrating public preferences into national coverage decision making. Reimbursement criteria considered outdated and changing societal expectations prompted the change. Both countries chose a deliberative process of public engagement with a multi-year commitment of many stakeholders to develop new reimbursement processes. Both countries' new reimbursement processes put a stronger emphasis on quality of life, the separation of individual versus societal perspectives, and the importance of final reimbursement decisions being taken in context rather than based largely on cost-effectiveness thresholds.ConclusionsTo face the growing financial pressure of sustainable funding of medicines, Belgium's and New Zealand's public payers have developed processes to engage the public in defining the reimbursement system's priorities. Although these countries differ in context and geographic location, they came up with overlapping lessons learnt which include the need for 1) political commitment to initiate change, 2) broad involvement of all stakeholders, and 3) commitment of all to engage in a long-term process. To evaluate these changes, further research is required to understand how coverage decisions in systems with and without public engagement differ.

Dataset Information

Personalizing Medical Treatment Decisions: Integrating Meta-analytic Treatment Comparisons with Patient-Specific Risks and Preferences.

Publications

Personalizing Medical Treatment Decisions: Integrating Meta-analytic Treatment Comparisons with Patient-Specific Risks and Preferences.

Similar Datasets

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