ArticleJAMA network open2023
Estimated Savings After Stopping Tyrosine Kinase Inhibitor Treatment Among Patients With Chronic Myeloid Leukemia.
Article in JAMA network open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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
5 citing papers in PubMed, 8 citations in OpenAlex.
- Improving quality of life for patients with chronic myeloid leukemia through supportive care, low-dose therapy, switching, and treatment-free remission.Haematologica · 2026Review
- Review
- Article
- Improving the Dosing Schedules of Targeted Anticancer Agents.Pharmaceuticals (Basel, Switzerland) · 2025Review
- Treatment-free remission after discontinuation of tyrosine kinase inhibitors in patients with chronic myeloid leukemia in the chronic phase: a systematic review and meta-analysis.Discover oncology · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
14 authors at 10 institutions in 1 country.
Funding
Abstract
Importance: Patients with chronic myeloid leukemia (CML) who have a sustained deep molecular response using tyrosine kinase inhibitors (TKIs) can safely attempt to stop their use. As these medications are very costly, this change in treatment protocols may result in large savings. Objective: To estimate future savings from attempting to stop TKI use among patients with CML who have deep molecular response. Design, Setting, and Participants: A microsimulation model was developed for this decision analytical modeling study to estimate costs for US adults moving from using a TKI, to attempting discontinuation and then reinitiating TKI therapy, if clinically appropriate. Estimates were calculated for US patients who currently have CML and simulated newly diagnosed cohorts of patients over the next 30 years. Exposure: Attempting to stop using a TKI. Main Outcomes and Measures: Estimated savings after attempted discontinuation of TKI use. Results: A simulated population of individuals with CML in 2018 and future populations were created using estimates from the SEER*Explorer website. The median age at diagnosis was 66 years for men and 65 years for women. Between 2022 and 2052, the savings associated with eligible patients attempting discontinuation of TKI therapy was estimated at more than $30 billion among those currently diagnosed and over $15 billion among those who will develop CML in the future, for a total savings of over $54 billion by 2052 for drug treatment and polymerase chain reaction testing. The estimate is conservative as it does not account for complications and other health care-associated costs for patients continuing TKI therapy. Conclusions and Relevance: The findings of this decision analytical modeling study of patients with CML suggest that attempting discontinuation of TKI therapy could save over $54 billion during the next 30 years. Further education for patients and physicians is needed to safely increase the number of patients who can successfully attain treatment-free remission.
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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.