ArticleInternational journal of clinical pharmacy2024
Evaluating the impact of PD-1 inhibitor treatment on key health outcomes for cancer patients in China.
Article in International journal of clinical pharmacy, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Systematic review of cost-effectiveness of Chinese PD-1/PD-L1 inhibitors as first-line treatment for hepatocellular carcinoma.BMC health services research · 2026Pooled it
- Cost-effectiveness analysis of sacituzumab tirumotecan vs. chemotherapy for patients with EGFR-TKI-resistant, EGFR-mutated advanced non-small cell lung cancer in China.Frontiers in public health · 2026Article
- Cost-effectiveness of tislelizumab versus sorafenib as first-line treatment for unresectable hepatocellular carcinoma: a comparative analysis in China, the United States and Europe.International journal of clinical pharmacy · 2025Article
- Cost-Effectiveness Analysis of Serplulimab Combined with Nab-Paclitaxel Plus Carboplatin Compared to Nab-Paclitaxel Plus Carboplatin Alone as First-Line Treatment for Advanced Squamous Non-Small Cell Lung Cancer in China.Risk management and healthcare policy · 2025Article
- Economic evaluation of camrelizumab plus rivoceranib versus sorafenib as first-line therapy for unresectable hepatocellular carcinoma in the United States and China.International journal of clinical pharmacy · 2024Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
backgroundThere is a lack of studies examining the influence of programmed cell death protein 1 (PD-1) inhibitors on the health outcomes of cancer patients in China.
aimThis study aimed to evaluate prospective health outcomes associated with introducing PD-1 inhibitor treatment in China over five years.
methodWe constructed a partitioned survival model to assess disparities in health outcomes over a 5-year time frame between two scenarios: one involving the availability of PD-1 inhibitor class with standard of care and the other involving standard of care alone. The impact on various health outcomes were assessed, including life years (LYs) gained, quality-adjusted life years (QALYs) gained, progression-free survival (PFS) years gained, the reduction in the number of grade 3-5 adverse events (AEs), and the improvement in objective remission rates (ORR). A sensitivity analysis was conducted to assess the robustness and reliability of the model.
resultsFrom 2023 to 2027, the incorporation of PD-1 inhibitor class treatments was anticipated to yield substantial improvements in health outcomes, with an estimated increase of 1,336,332 LYs (+ 24.7%), 1,065,359 QALYs (+ 30.3%), and 1,177,564 PFS years (+ 57.4%) compared to standard of care alone. Simultaneously, the number of grade 3-5 AEs decreased by 334,976 (- 13.0%), and the ORR saw a 19.1% increase (+ 105.6%) relative to standard of care treatment alone.
conclusionThis study provides a analysis of the potential beneficial effects on health outcomes in the Chinese population after introducing PD-1 inhibitor class treatment. The findings suggest the PD-1 inhibitor class will significantly improve patient survival.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.