ReviewCancers2024
Cost-Effectiveness of Treatment Optimisation with Biomarkers for Immunotherapy in Solid Tumours: A Systematic Review.
Review in Cancers, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
10 citing papers in PubMed, 1 synthesis or guideline pooled it, 11 citations in OpenAlex.
- The safety and efficacy of binimetinib for lung cancer: a systematic review.BMC pulmonary medicine · 2024Pooled it
- Towards liquid biopsy-based analysis of antitumour immunity.Nature reviews. Clinical oncology · 2026Review
- Emerging diagnostic biomarkers and therapeutic targets in Alzheimer's disease.Inflammopharmacology · 2026Review
- Guiding the Application of Immunotherapy in Nonsmall Cell Lung Cancer: The Role of Biomarkers.Thoracic cancer · 2026Review
- Article
- Biomarkers of treatment response in rheumatoid arthritis: from conventional markers to tissue immunophenotype.Frontiers in immunology · 2026Review
- The economic value of mismatch repair-guided immunotherapy in endometrial cancer: companion testing and patient selection.Frontiers in medicine · 2026Review
- Plying potency assays for immunotherapy of solid tumors.Frontiers in immunology · 2026Review
- The promise of PD1/PDL1 targeted immunotherapy in locally advanced cervical cancer: a game-changer for patients outcome?Frontiers in immunology · 2025Review
- Quality-of-life scale machine learning approach to predict immunotherapy response in patients with advanced non-small cell lung cancer.Frontiers in immunology · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 4 institutions in 1 country.
Funding
Abstract
This study investigated the health economic evaluations of predictive biomarker testing in solid tumours treated with immune checkpoint inhibitors (ICIs). Searching PubMed, EMBASE, and Web of Science from June 2010 to February 2022, 58 relevant articles were reviewed out of the 730 screened. The focus was predominantly on non-small cell lung cancer (NSCLC) (65%) and other solid tumours (40%). Among the NSCLC studies, 21 out of 35 demonstrated cost-effectiveness, notably for pembrolizumab as first-line treatment when preceded by PD-L1 assessment, cost-effective at a threshold of $100,000/QALY compared to the standard of care. However, for bladder, cervical, and triple-negative breast cancers (TNBCs), no economic evaluations met the affordability threshold of $100,000/QALY. Overall, the review highlights a certain degree of uncertainty about the cost-effectiveness of ICI. In particular, we found PD-L1 expression associated with ICI treatment to be a cost-effective strategy, particularly in NSCLC, urothelial, and renal cell carcinoma. The findings suggest the potential value of predictive biomarker testing, specifically with pembrolizumab in NSCLC, while indicating challenges in achieving cost-effectiveness for certain other solid tumours.
Indexed as
Identifiers
What OpenQuestion holds
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.