Evidence map›Paper›PMID 28767139›Full record

SynthesisJournal of surgical oncology2017

Personalizing prognosis in colorectal cancer: A systematic review of the quality and nature of clinical prognostic tools for survival outcomes.

Alyson L Mahar, Carolyn Compton, Susan Halabi, Kenneth R Hess, Martin R Weiser, Patti A Groome

Abstract readSystematic Review
In one paragraph

Synthesis in Journal of surgical oncology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 81 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
81citing papers in PubMed, 4 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

81 citing papers in PubMed, 4 syntheses or guidelines pooled it.

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  17. Multimarker Assessment of B-Cell and Plasma Cell Subsets and Their Prognostic Role in the Colorectal Cancer Microenvironment.Clinical cancer research : an official journal of the American Association for Cancer Research · 2025
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  19. Observational
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21 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Alyson L MaharDivision of Cancer Care and Epidemiology, Cancer Research Institute, Queen's University, Ontario, Canada.ORCID http://orcid.org/0000-0002-6862-3760
Carolyn ComptonProfessor Life Sciences, Arizona State University and Professor of Laboratory Medicine and Pathology, Mayo Clinic School of Medicine, Rochester, Minnesota.
Susan HalabiDepartment of Biostatistics and Bioinformatics, Duke University and Alliance Statistics and Data Center, Durham, North Carolina.
Kenneth R HessDepartment of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Martin R WeiserMemorial Sloan Kettering Cancer Center, New York, New York.
Patti A GroomeDivision of Cancer Care and Epidemiology, Cancer Research Institute, Queen's University, Ontario, Canada.

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Hongbiao Carl Lekaye · 1985 to 2026
$347.4M
NCI NIH HHS P30 CA008748
6 · The paper itself

Abstract

Integrating diverse types of prognostic information into accurate, individualized estimates of outcome in colorectal cancer is challenging. Significant heterogeneity in colorectal cancer prognostication tool quality exists. Methodology is incompletely or inadequately reported. Evaluations of the internal or external validity of the prognostic model are rarely performed. Prognostication tools are important devices for patient management, but tool reliability is compromised by poor quality. Guidance for future development of prognostication tools in colorectal cancer is needed.

Indexed as

Colorectal NeoplasmsHumansNeoplasm StagingPrognosisclinical prediction toolcolorectal neoplasmsnomogramprognosis

Identifiers

PMID28767139
PMCPMC5760443

What OpenQuestion holds

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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.