ArticleCancer2015
Provider-based research networks may improve early access to innovative colon cancer treatment for African Americans treated in the community.
Article in Cancer, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed, 1 synthesis or guideline pooled it, 8 citations in OpenAlex.
- If health organisations and staff engage in research, does healthcare improve? Strengthening the evidence base through systematic reviews.Health research policy and systems · 2024Pooled it
- Tracing the potential of networks to improve community cancer care: an in-depth single case study.Implementation science communications · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 1 institution in 1 country.
Funding
Abstract
backgroundAfrican American (AA) patients with colon cancer (CC) experience worse outcomes than whites partly due to differential treatment. The National Cancer Institute's Community Clinical Oncology Program (CCOP), a provider-based research network, adopts and diffuses innovative CC treatments quickly. The authors hypothesized that CCOP participation would lessen racial differences in the receipt of oxaliplatin, an innovative treatment for CC, among patients with stage III CC in the community.
methodsUsing Surveillance, Epidemiology, and End Results (SEER)-Medicare data, the authors performed a population-based retrospective cohort study of AA and white individuals aged ≥66 years who were diagnosed with AJCC stage III CC from 2003 through 2005. Generalized estimating equations were used to calculate the odds of receiving an oxaliplatin-containing regimen. Predicted probabilities of oxaliplatin receipt for race-CCOP combinations were calculated. The absolute difference in oxaliplatin receipt between races was estimated using the interaction contrast ratio.
resultsOf 2971 included individuals, 36% received oxaliplatin, 29.5% were CCOP-affiliated, and 7.6% were AA. On multivariate analysis, early diffusion of oxaliplatin was not found to be associated with race or CCOP participation. The probability of receiving oxaliplatin for AAs participating in a CCOP (0.46) was nearly double that of AAs who were not participating in a CCOP (0.25; P <.05). For white individuals, the probabilities of receiving oxaliplatin did not differ by CCOP participation. For oxaliplatin receipt, the joint effects assessment suggested a greater benefit of CCOP participation among AAs (interaction contrast ratio, 1.7).
conclusionsAmong older patients with stage III CC, there is a differential impact of race on oxaliplatin receipt depending on CCOP participation. AAs treated by CCOPs were more likely to receive oxaliplatin than AAs treated elsewhere. Provider-based research networks may facilitate early access to innovative treatment for AAs with stage III CC.
Indexed as
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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.