Evidence map›Paper›PMID 37879723›Full record

ArticleBMJ (Clinical research ed.)2023

Pharmaceutical industry payments and delivery of non-recommended and low value cancer drugs: population based cohort study.

Aaron P Mitchell, Stacie B Dusetzina, Akriti Mishra Meza, Niti U Trivedi, Peter B Bach, Aaron N Winn

Open access · hybridAbstract read
In one paragraph

Article in BMJ (Clinical research ed.), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
22.8field-weighted citation impact, top 1% of its field
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed, 40 citations in OpenAlex.

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  7. Use of Low-Value Cancer Treatments in Medicare Advantage Versus Traditional Medicare.Journal of clinical oncology : official journal of the American Society of Clinical Oncology · 2025
    Article
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  16. Revisiting Alma Ata: A Blueprint for Cancer Care.Cancer control : journal of the Moffitt Cancer Center
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors at 3 institutions in 1 country.

Aaron P MitchellDepartment of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY 10017, USA mitchea2@mskcc.org.ORCID 0000-0003-3639-3515
Stacie B DusetzinaDepartment of Health Policy and Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA.ORCID 0000-0002-3907-9196
Akriti Mishra MezaDepartment of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY 10017, USA.ORCID 0000-0002-3477-5037
Niti U TrivediDelfi Diagnostics, Baltimore, MD, USA.ORCID 0000-0002-3967-6492
Peter B BachDelfi Diagnostics, Baltimore, MD, USA.ORCID 0000-0003-2906-3913
Aaron N WinnUniversity of Illinois Chicago, Chicago, IL, USA.
Memorial Sloan Kettering Cancer Center · USUniversity of Illinois Chicago · USVanderbilt University Medical Center · US

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Hongbiao Carl Lekaye · 1985 to 2026
$347.4M
Understanding the Importance of Industry Relationships for Cancer Care Quality, Outcomes, and CostsR37CA264563 · NCI · SLOAN-KETTERING INST CAN RESEARCH · PI Aaron P Mitchell · 2022 to 2026
$2.0M
NCI NIH HHS P30 CA008748NCI NIH HHS R37 CA264563
6 · The paper itself

Abstract

objectiveTo estimate the association between oncologists' receipt of payments from the pharmaceutical industry and delivery of non-recommended or low value interventions among their patients.

designCohort study.

settingFee-for-service Medicare claims.

participantsMedicare beneficiaries with a diagnosis of incident cancer (new occurrence of a cancer diagnosis code in proximity to claims for cancer treatment, and no such diagnosis codes during a ≥1 year washout period) during 2014-19, who met additional requirements identifying them as at risk for one of four non-recommended or low value interventions: denosumab for castration sensitive prostate cancer, granulocyte colony stimulating factors (GCSF) for patients at low risk for neutropenic fever, nab-paclitaxel for cancers with no evidence of superiority over paclitaxel, and a branded drug in settings where a generic or biosimilar version was available.

main outcome measuresReceipt of the non-recommended or low value drug for which the patient was at risk. The primary association of interest was the assigned oncologist's receipt of any general payments from the manufacturer of the corresponding non-recommended or low value drug (measured in Open Payments) within 365 days before the patient's index cancer date. The two modeling approaches used were general linear model controlling for patients' characteristics and calendar year, and general linear model with physician level indicator variables.

resultsOncologists were in receipt of industry payments for 2962 of 9799 patients (30.2%) at risk for non-recommended denosumab (median $63), 76 747 of 271 485 patients (28.3%) at risk for GCSF (median $60); 18 491 of 86 394 patients (21.4%) at risk for nab-paclitaxel (median $89), and 4170 of 13 386 patients (31.2%) at risk for branded drugs (median $156). The unadjusted proportion of patients who received non-recommended denosumab was 31.4% for those whose oncologist had not received payment and 49.5% for those whose oncologist had (prevalence difference 18.0%); the corresponding values for GCSF were 26.6%

conclusionsWithin some clinical scenarios, industry payments to physicians are associated with non-recommended and low value drugs. These findings raise quality of care concerns about the financial relationships between physicians and industry.

Indexed as

Antineoplastic AgentsNeoplasmsAgedCohort StudiesDenosumabDrug IndustryHumansMaleMedicareUnited StatesAntineoplastic AgentsDenosumab

Identifiers

PMID37879723
PMCPMC10599253
OpenAlexW4387932639

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.