Evidence map›Paper›PMID 29135615›Full record

Observational studyMedical care2018

Diffusion of Bevacizumab Across Oncology Practices: An Observational Study.

Nancy L Keating, Haiden A Huskamp, Deborah Schrag, John M McWilliams, Barbara J McNeil, Bruce E Landon, Michael E Chernew, Sharon-Lise T Normand

Abstract readObservational Study
In one paragraph

Observational study in Medical care, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

15 citing papers in PubMed, 1 synthesis or guideline pooled it.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Nancy L KeatingDepartment of Health Care Policy, Harvard Medical School.
Haiden A HuskampDepartment of Health Care Policy, Harvard Medical School.
Deborah SchragBrigham and Women's Hospital, Department of Medical Oncology, Dana-Farber Cancer Institute.
John M McWilliamsDepartment of Health Care Policy, Harvard Medical School.
Barbara J McNeilDepartment of Health Care Policy, Harvard Medical School.
Bruce E LandonDepartment of Health Care Policy, Harvard Medical School.
Michael E ChernewDepartment of Health Care Policy, Harvard Medical School.
Sharon-Lise T NormandDepartment of Health Care Policy, Harvard Medical School.

Funding

Technology Diffusion PathwaysU01MH103018 · NIMH · HARVARD MEDICAL SCHOOL · PI HUSKAMP, HAIDEN A., NORMAND, SHARON-LISE TERESA · 2013 to 2017
$2.7M
Behavioral Economics and Improving Chemotherapy Decisions for Advanced CancerK24CA181510 · NCI · HARVARD MEDICAL SCHOOL · PI KEATING, NANCY L · 2014 to 2018
$867k
NCI NIH HHS K24 CA181510NIMH NIH HHS U01 MH103018
6 · The paper itself

Abstract

backgroundTechnological advances can improve care and outcomes but are a primary driver of health care spending growth. Understanding diffusion and use of new oncology therapies is important, given substantial increases in prices and spending on such treatments.

objectivesExamine diffusion of bevacizumab, a novel (in 2004) and high-priced biologic cancer therapy, among US oncology practices during 2005-2012 and assess variation in use across practices. RESEARCH

designPopulation-based observational study.

settingA total of 2329 US practices providing cancer chemotherapy.

participantsRandom 20% sample of 236,304 Medicare fee-for-service beneficiaries aged above 65 years in 2004-2012 undergoing infused chemotherapy for cancer. MEASURES: Diffusion of bevacizumab (cumulative time to first use and 10% use) in practices, variation in use across practices overall and by higher versus lower-value use. We used hierarchical models with practice random effects to estimate the between-practice variation in the probability of receiving bevacizumab and to identify factors associated with use.

resultsWe observed relatively rapid diffusion of bevacizumab, particularly in independent practices and larger versus smaller practices. We observed substantial variation in use; the adjusted odds ratio (95% confidence interval) of bevacizumab use was 2.90 higher (2.73-3.08) for practices 1 SD above versus one standard deviation below the mean. Variation was less for higher-value [odds ratio=2.72 (2.56-2.89)] than lower-value uses [odds ratio=3.61 (3.21-4.06)].

conclusionsUse of bevacizumab varied widely across oncology practices, particularly for lower-value indications. These findings suggest that interventions targeted to practices have potential for decreasing low-value use of high-cost cancer therapies.

Indexed as

AgedAntineoplastic Agents, ImmunologicalBevacizumabFee-for-Service PlansFemaleHumansMaleMedical OncologyMedicareNeoplasmsOdds RatioPractice Patterns, Physicians'United StatesAntineoplastic Agents, ImmunologicalBevacizumab

Identifiers

PMID29135615
PMCPMC5726588

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Registered trials

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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.