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Record W4417299894 · doi:10.1080/13696998.2025.2599670

Impact of pembrolizumab on health outcomes and productivity in earlier-stage cancers within the US Medicare population

2025· article· en· W4417299894 on OpenAlexfundno aff
Yizhen Lai, Sameer A. Greenall, Joe Taylor, Catarina Neves

Bibliographic record

VenueJournal of Medical Economics · 2025
Typearticle
Languageen
FieldMedicine
TopicCancer Immunotherapy and Biomarkers
Canadian institutionsnot available
FundersMerck CanadaMerck
KeywordsPembrolizumabProductivityPopulationInvestment (military)Work productivityExploratory analysis

Abstract

fetched live from OpenAlex

AIM: Pembrolizumab has demonstrated significant improvements in clinical outcomes across multiple cancers. This study quantifies health benefits and productivity gains of pembrolizumab as a perioperative/adjuvant treatment in five earlier-stage cancer indications (melanoma stage IIB-C and III, triple-negative breast cancer, renal cell carcinoma, resectable and resected non-small cell lung cancer) within the US Medicare beneficiary population. MATERIALS AND METHODS: A population-level, multi-indication decision model was developed to project the health and productivity gains of pembrolizumab. Over the 10 year period (2025-2034), a new patient cohort enters the model each year, and every cohort is followed through to 2034. Two scenarios were compared for cohorts of Medicare beneficiaries newly eligible for perioperative/adjuvant pembrolizumab: (1) a world without pembrolizumab, using only historical perioperative/adjuvant treatment options, and (2) a world where pembrolizumab is added as perioperative/adjuvant therapy for FDA-approved cancers. Outcomes included life years (LYs), quality-adjusted LYs (QALYs), number of events or recurrences, number of systemic treatments for metastatic disease, deaths, and caregivers' productive years lost. Inputs include clinical trial efficacy, Medicare and US population data, epidemiology, and market share information. RESULTS: Adding perioperative/adjuvant pembrolizumab is projected to increase recurrence-free LYs by 122,918 (+10%), total LYs by 56,704 (+4%), and QALYs by 55,483 (+4%). This strategy could reduce the number of recurrences by 35,558 (-16%), number of systemic treatments for metastatic disease by 32,962 (-16%), deaths following the first recurrence by 8,962 (-10%), and total deaths by 16,146 (-11%). Caregivers' productive years lost are estimated to decline by 9,392 (-18%) through reduced absenteeism and presenteeism. CONCLUSIONS: Perioperative/adjuvant pembrolizumab in earlier-stage cancers can meaningfully improve clinical outcomes for Medicare patients and reduce caregiver productivity losses. Sustained investment and access to pembrolizumab are critical to fully realize these benefits for patients and society.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.095
Threshold uncertainty score0.526

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.016
GPT teacher head0.347
Teacher spread0.331 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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