Evidence map›Paper›PMID 39546402›Full record

ArticleCancer medicine2024

Establishment and Validation of a Prognostic Nomogram for Predicting Postoperative Overall Survival in Advanced Stage III-IV Colorectal Cancer Patients.

Pengwei Lou, Dongmei Luo, Yuting Huang, Chen Chen, Shuai Yuan, Kai Wang

Abstract readValidation Study
In one paragraph

Article in Cancer medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

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

  1. 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

6 authors.

Pengwei LouDepartment of Big Data, College of Information Engineering, Xinjiang Institute of Engineering, Urumqi, Xinjiang Uygur Autonomous Region, People's Republic of China.ORCID https://orcid.org/0009-0005-5939-0626
Dongmei LuoDepartment of Medical Administration, Cancer Hospital Affiliated With Xinjiang Medical University, Urumqi, Xinjiang Uygur Autonomous Region, People's Republic of China.
Yuting HuangDepartment of Medical Administration, Traditional Chinese Medicine Hospital Affiliated With Xinjiang Medical University, Urumqi, Xinjiang Uygur Autonomous Region, People's Republic of China.
Chen ChenCollege of Public Health, Xinjiang Medical University, Urumqi, Xinjiang Uygur Autonomous Region, People's Republic of China.
Shuai YuanDepartment of Urology, Cancer Hospital Affiliated With Xinjiang Medical University, Urumqi, Xinjiang Uygur Autonomous Region, People's Republic of China.
Kai WangCollege of Public Health, Xinjiang Medical University, Urumqi, Xinjiang Uygur Autonomous Region, People's Republic of China.

Funding

China's health care policy on clinical decision-making and patient access research 20230613The 14-th Five-Year Plan Distinctive Program of Public Health and Preventive Medicine in Higher Education Institutions of Xinjiang Uygur Autonomous RegionThe Key R&D Program of Xinjiang Uygur Autonomous Region 2023B03002The major science and technology projects of Xinjiang Autonomous Region 2022A03019-1
6 · The paper itself

Abstract

backgroundMost colorectal cancer (CRC) patients are at an advanced stage when they are first diagnosed. Risk factors for predicting overall survival (OS) in advanced stage CRC patients are crucial, and constructing a prognostic nomogram model is a scientific method for survival analysis.

methodsA total of 2956 advanced stage CRC patients were randomised into training and validation groups at a 7:3 ratio. Univariate and multivariate Cox proportional hazards regression analyses were used to screen risk factors for OS and subsequently construct a prognostic nomogram model for predicting 1-, 3-, 5-, 8- and 10-year OS of advanced stage CRC patients. The performance of the model was demonstrated by the area under the curve (AUC) values, calibration curves and decision curve analysis (DCA). Kaplan-Meier curves were used to plot the survival probabilities for different strata of each risk factor.

resultsThere was no statistically significant difference (p > 0.05) in the 32 clinical variables between patients in the training and validation groups. Univariate and multivariate Cox proportional hazards regression analyses demonstrated that age, location, TNM, chemotherapy, liver metastasis, lung metastasis, MSH6, CEA, CA199, CA125 and CA724 were risk factors for OS. We estimated the AUC values for the nomogram model to predict 1-, 3-, 5-, 8- and 10-year OS, which in the training group were 0.826 (95% CI: 0.807-0.845), 0.836 (0.819-0.853), 0.839 (0.820-0.859), 0.835 (0.809-0.862) and 0.825 (0.779-0.870) respectively; in the validation group, the corresponding AUC values were 0.819 (0.786-0.852), 0.831 (0.804-0.858), 0.830 (0.799-0.861), 0.815 (0.774-0.857) and 0.802 (0.723-0.882) respectively. Finally, the 1-, 3-, 5-, 8- and 10-year OS rates for advanced stage CRC patients were 73.4 (71.8-75.0), 49.5 (47.8-51.4), 43.3 (41.5-45.2), 40.1 (38.1-41.9) and 38.6 (36.6-40.8) respectively.

conclusionWe constructed and validated an original nomogram for predicting the postoperative OS of advanced stage CRC patients, which can help facilitates physicians to accurately assess the individual survival of postoperative patients and identify high-risk patients.

Indexed as

Colorectal NeoplasmsNeoplasm StagingNomogramsAdultAgedFemaleHumansKaplan-Meier EstimateMaleMiddle AgedPostoperative PeriodPrognosisProportional Hazards ModelsRisk Factorscolorectal cancernomogramoverall survivalprognosis

Identifiers

PMID39546402
PMCPMC11566917

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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.