Evidence map›Paper›PMID 36803500›Full record

ArticleBMC medicine2023

Prediction models of colorectal cancer prognosis incorporating perioperative longitudinal serum tumor markers: a retrospective longitudinal cohort study.

Chunxia Li, Ke Zhao, Dafu Zhang, Xiaolin Pang, Hongjiang Pu, Ming Lei, Bingbing Fan, Jiali Lv, Dingyun You, Zhenhui Li and 1 more

Open access · goldAbstract read
In one paragraph

Article in BMC medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.

0numbers the graph read from it
0cells of the map it votes in
39citing papers in PubMed
12.7field-weighted citation impact, top 1% 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

39 citing papers in PubMed, 55 citations in OpenAlex.

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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

11 authors at 4 institutions in 1 country.

Chunxia Li *Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, 44 Wenhuaxi Road, PO Box 100, Jinan, 250012, Shandong, China.
Ke Zhao *Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China.
Dafu ZhangDepartment of Radiology, the Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Yunnan Cancer Center, No.519 Kunzhou Road, Xishan District, Kunming, 650118, Yunnan, China.
Xiaolin PangDepartment of Radiotherapy, the Sixth Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 510655, China.
Hongjiang PuDepartment of Colorectal Surgery, the Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Yunnan Cancer Center, Kunming, 650118, China.
Ming LeiDepartment of Clinical Laboratory Medicine, the Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Yunnan Cancer Center, Kunming, 650118, China.
Bingbing FanDepartment of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, 44 Wenhuaxi Road, PO Box 100, Jinan, 250012, Shandong, China.
Jiali LvDepartment of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, 44 Wenhuaxi Road, PO Box 100, Jinan, 250012, Shandong, China.
Dingyun YouSchool of Biomedical Engineering Research, Kunming Medical University, No.1168 Chunrongxi Road, Chenggong District, Kunming, 650500, Yunnan, China. youdingyun@qq.com.
Zhenhui LiDepartment of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China. lizhenhui621@qq.com.
Tao ZhangDepartment of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, 44 Wenhuaxi Road, PO Box 100, Jinan, 250012, Shandong, China. taozhang@sdu.edu.cn.ORCID 0000-0003-1048-4443
Kunming Medical University · CNShandong University · CNGuangdong Academy of Medical Sciences · CNSun Yat-sen University · CN

Funding

National Natural Science Foundation of China 81973147National Natural Science Foundation of China 82001986National Natural Science Foundation of China 82073569National Natural Science Foundation of China 82222064
6 · The paper itself

Abstract

backgroundCurrent prognostic prediction models of colorectal cancer (CRC) include only the preoperative measurement of tumor markers, with their available repeated postoperative measurements underutilized. CRC prognostic prediction models were constructed in this study to clarify whether and to what extent the inclusion of perioperative longitudinal measurements of CEA, CA19-9, and CA125 can improve the model performance, and perform a dynamic prediction.

methodsThe training and validating cohort included 1453 and 444 CRC patients who underwent curative resection, with preoperative measurement and two or more measurements within 12 months after surgery, respectively. Prediction models to predict CRC overall survival were constructed with demographic and clinicopathological variables, by incorporating preoperative CEA, CA19-9, and CA125, as well as their perioperative longitudinal measurements.

resultsIn internal validation, the model with preoperative CEA, CA19-9, and CA125 outperformed the model including CEA only, with the better area under the receiver operating characteristic curves (AUCs: 0.774 vs 0.716), brier scores (BSs: 0.057 vs 0.058), and net reclassification improvement (NRI = 33.5%, 95% CI: 12.3 ~ 54.8%) at 36 months after surgery. Furthermore, the prediction models, by incorporating longitudinal measurements of CEA, CA19-9, and CA125 within 12 months after surgery, had improved prediction accuracy, with higher AUC (0.849) and lower BS (0.049). Compared with preoperative models, the model incorporating longitudinal measurements of the three markers had significant NRI (40.8%, 95% CI: 19.6 to 62.1%) at 36 months after surgery. External validation showed similar results to internal validation. The proposed longitudinal prediction model can provide a personalized dynamic prediction for a new patient, with estimated survival probability updated when a new measurement is collected during 12 months after surgery.

conclusionsPrediction models including longitudinal measurements of CEA, CA19-9, and CA125 have improved accuracy in predicting the prognosis of CRC patients. We recommend repeated measurements of CEA, CA19-9, and CA125 in the surveillance of CRC prognosis.

Indexed as

Biomarkers, TumorColorectal NeoplasmsCA-125 AntigenCA-19-9 AntigenCarcinoembryonic AntigenHumansLongitudinal StudiesPrognosisRetrospective StudiesBiomarkers, TumorCA-125 AntigenCA-19-9 AntigenCarcinoembryonic AntigenColorectal cancerDynamic predictionOverall survivalPerioperative serum tumor markers

Identifiers

PMID36803500
PMCPMC9942392
OpenAlexW4321366453

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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.