Evidence map›Paper›PMID 32150269›Full record

ArticleJAMA network open2020

Cost-effectiveness Evaluation of Targeted Surgical and Endoscopic Therapies for Early Colorectal Adenocarcinoma Based on Biomarker Profiles.

Se Ryeong Jang, Han Truong, Aaron Oh, Jin Choi, Angela C Tramontano, Monika Laszkowska, Chin Hur

Open access · goldAbstract read
In one paragraph

Article in JAMA network open, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
0.3field-weighted citation impact, top 44% 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

5 citing papers in PubMed, 1 synthesis or guideline pooled it, 9 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors at 4 institutions in 1 country.

Se Ryeong JangDepartment of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York.
Han TruongHerbert Irving Comprehensive Cancer Center, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York.
Aaron OhHerbert Irving Comprehensive Cancer Center, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York.
Jin ChoiHerbert Irving Comprehensive Cancer Center, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York.
Angela C TramontanoInstitute for Technology Assessment, Massachusetts General Hospital, Harvard Medical School, Boston.
Monika LaszkowskaDepartment of Medicine, New York Presbyterian/Columbia University Medical Center, New York, New York.
Chin HurDepartment of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York.
Columbia University · USColumbia University Irving Medical Center · USMassachusetts General Hospital · USThomas Jefferson University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Importance: Colorectal cancer (CRC) is the second leading cause of cancer-related mortality in the United States. The prognosis for patients with CRC varies widely, but new prognostic biomarkers provide the opportunity to implement a more individualized approach to treatment selection. Objective: To assess the cost-effectiveness of 3 therapeutic strategies, namely, endoscopic therapy (ET), laparoscopic colectomy (LC), and open colectomy (OC), for patients with T1 CRC with biomarker profiles that prognosticate varying levels of tumor progression in the US payer perspective. Design, Setting, and Participants: In this economic evaluation study, a Markov model was developed for the cost-effectiveness analysis. Risks of all-cause mortality and recurrent cancer after ET, LC, or OC were estimated with a 35-year time horizon. Quality of life was based on EuroQoL 5 Dimensions scores reported in the published literature. Hospital and treatment costs reflected Medicare reimbursement rates. Deterministic and probabilistic sensitivity analyses were performed. Data from patients with T1 CRC and 6 biomarker profiles that included adenomatous polyposis coli (APC), TP53 and/or KRAS, or BRAFV600E were used as inputs for the model. Data analyses were conducted from February 27, 2019, to May 13, 2019. Exposures: Endoscopic therapy, LC, and OC. Main Outcomes and Measures: The primary outcomes were unadjusted life-years, quality-adjusted life-years (QALYs), and the incremental cost-effectiveness ratio (ICER) between competing treatment strategies. Results: Endoscopic therapy had the highest QALYs and the lowest cost and was the dominant treatment strategy for T1 CRC with the following biomarker profiles: BRAFV600E, APC(1)/KRAS/TP53, APC(2) or APC(2)/KRAS or APC(2)/TP53, or APC(1) or APC(1)/KRAS or APC(1)/TP53. The QALYs gained ranged from 16.97 to 17.22, with costs between $68 902.75 and $77 784.53 in these subgroups. For the 2 more aggressive biomarker profiles with worse prognoses (APC(2)/KRAS/TP53 and APCwt [wild type]), LC was the most effective strategy (with 16.45 and 16.61 QALYs gained, respectively) but was not cost-effective. Laparoscopic colectomy cost $65 234.87 for APC(2)/KRAS/TP53 and $71 250.56 for APCwt, resulting in ICERs of $113 290 per QALY and $178 765 per QALY, respectively. Conclusions and Relevance: This modeling analysis found that ET was the most effective strategy for patients with T1 CRC with less aggressive biomarker profiles. For patients with more aggressive profiles, LC was more effective but was costly, rendering ET the cost-effective option. This study highlights the potential utility of prognostic biomarkers in T1 CRC treatment selection.

Indexed as

AdenocarcinomaColorectal NeoplasmsEndoscopy, GastrointestinalAgedBiomarkers, TumorCost-Benefit AnalysisFemaleHumansMaleMiddle AgedTreatment OutcomeBiomarkers, Tumor

Identifiers

PMID32150269
PMCPMC7063501
OpenAlexW3009069808

What OpenQuestion holds

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LicenceCC BY
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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.