Evidence map›Paper›PMID 36420093›Full record

ArticleBioMed research international2022

Prognostic Nomogram for Gastrointestinal Stromal Tumors after Surgery Based on the SEER Database.

Qianhui Sun, Yunru Chen, Tingting Li, Xiaoyu Zhu, Guanghui Zhu, Baoyi Ni, Ruike Gao, Jie Li

Abstract read
In one paragraph

Article in BioMed research international, 2022. 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
–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

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

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4 · The record

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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

8 authors.

Qianhui SunOncology Department, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China 100053.
Yunru ChenCentre for Evidence-Based Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China 100029.
Tingting LiBeijing University of Chinese Medicine, Beijing, China 100029.
Xiaoyu ZhuOncology Department, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China 100053.
Guanghui ZhuOncology Department, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China 100053.
Baoyi NiOncology Department, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China 100053.
Ruike GaoOncology Department, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China 100053.
Jie LiOncology Department, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China 100053.ORCID https://orcid.org/0000-0002-3461-8816

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We aimed to determine prognostic factors and develop an effective and practical nomogram for predicting cancer-specific survival in gastrointestinal stromal tumor (GIST) patients. Postoperative data were obtained from the SEER database (2000-2018). Patients were divided into training and validation cohorts at random (7 : 3). Prognostic factors were screened, and a prognostic nomogram was established using log-rank testing and Cox regression. We used DCA, ROC curves, C-index, and calibration curves to evaluate our model's predictive performance. The clinical value of the nomogram and the modified National Institute of Health (M-NIH) classification were compared using the NRI and IDI. The Kaplan-Meier method was applied to examine survival by risk group, and log-rank tests were applied to compare variations in survival curves. Independent prognostic risk factors associated with cancer-specific survival on multivariate Cox proportional hazards regression analysis were age, race, and tumor location, size, grade, and stage. Clinically relevant variables need to be considered in addition to statistically significant variables when developing prognostic models to aid clinical decision-making. We included two additional variables (mitotic rate and chemotherapy) when constructing the prognostic model. The C-index was 0.766 (95% confidence interval (CI): 0.737-0.794) in the training cohort and 0.795 (95% CI: 0.754-0.836) in the internal validation group suggesting robustness. The areas under the ROC curve for three-year and five-year survival were >0.700, indicating satisfactory discrimination. The calibration curves showed good agreement between the predictions of the nomogram and the actual results. The NRI (0.346 for 3-year and 0.265 for 5-year cancer-specific survival for patients with GIST (GSS) prediction; validation cohort: 0.356 for 3-year and 0.246 for 5-year GSS prediction) and IDI values (0.047 for 3-year and 0.060 for 5-year GSS prediction; validation cohort: 0.071 for 3-year and 0.084 for 5-year GSS prediction) suggested that the established nomogram performed significantly better than the M-NIH classification. The DCA indicated that the nomogram was clinically useful and had a high discriminative ability in identifying patients who were at high risk of poor outcomes. According to nomogram findings, patients were divided into three groups (high, moderate, and low risk), with significantly different prognoses in both cohorts. Our nomogram satisfactorily predicted survival in postsurgical GIST patients, which may assist clinicians to evaluate the postoperative status and guide subsequent treatments.

Indexed as

Gastrointestinal Stromal TumorsNomogramsHumansPrognosisProportional Hazards ModelsSEER Program

Identifiers

PMID36420093
PMCPMC9678471

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