Evidence map›Paper›PMID 33186890›Full record

ArticleTranslational oncology2021

Prediction of cancer-specific survival and overall survival in middle-aged and older patients with rectal adenocarcinoma using a nomogram model.

Hao Liu, Liang Lv, Yidan Qu, Ziweng Zheng, Junjiang Zhao, Bo Liu, Dasen Zhang, Hexiang Wang, Jian Zhang

Open access · goldAbstract read
In one paragraph

Article in Translational oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
0.8field-weighted citation impact, top 26% 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

9 citing papers in PubMed, 14 citations in OpenAlex.

  1. Trial
  2. Trial
  3. Article
  4. Elderly Rectal Cancer: An Updated Review.Current oncology reports · 2024
    Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
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

9 authors at 2 institutions in 1 country.

Hao LiuGeneral Surgery Department, Affiliated Hospital of Qingdao University, Qingdao, Shandong, China.
Liang LvGeneral Surgery Department, Affiliated Hospital of Qingdao University, Qingdao, Shandong, China.
Yidan QuRheumatology and Immunology Department, Affiliated Hospital of Qingdao University, Qingdao, Shandong, China.
Ziweng ZhengGeneral Surgery Department, Affiliated Hospital of Qingdao University, Qingdao, Shandong, China.
Junjiang ZhaoGeneral Surgery Department, Affiliated Hospital of Qingdao University, Qingdao, Shandong, China.
Bo LiuGeneral Surgery Department, Affiliated Hospital of Qingdao University, Qingdao, Shandong, China.
Dasen ZhangGeneral Surgery Department, Zaozhuang Municipal Hospital, Qingdao, Shandong, China.
Hexiang WangRadiology Department, Affiliated Hospital of Qingdao University, Qingdao, Shandong, China. Electronic address: 18661808669@126.com.
Jian ZhangGeneral Surgery Department, Affiliated Hospital of Qingdao University, Qingdao, Shandong, China. Electronic address: drjianzhang@126.com.
Qingdao University · CNZaozhuang Municipal Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo develop a new nomogram tool for predicting survival in middle-aged and elderly patients with rectal adenocarcinoma.

methodsA total of 6,116 patients were randomly assigned in a 7:3 ratio to training and validation cohorts. Univariate and multivariate Cox proportional hazards regression analyses were used to identify independent prognostic factors associated with overall survival (OS) and cancer-specific survival (CSS) in the training set, and two nomogram prognostic models were constructed. The validity, accuracy, discrimination, predictive ability, and clinical utility of the models were assessed based on the concordance index (C-index), area under the receiver operating characteristics (ROC) curve, time-dependent area under the ROC curve (AUC), Kaplan-Meier survival curve, and decision curve analyses.

resultsPredictors of OS and CSS were identified, and nomograms were successfully constructed. The calibration discrimination for both the OS and CSS nomogram prediction models was good (C-index: 0.763 and 0.787, respectively). The AUC showed excellent predictive performance, and the calibration curve exhibited significant predictive power for both nomograms. The time-dependent AUC showed that the predictive ability of the predictor-based nomogram was better than that of the TNM stage. The nomograms successfully discriminated high-, medium-, and low-risk patients for all-cause and cancer-specific mortality. The decision curve demonstrated that the nomograms are useful with respect to good decision power.

conclusionOur nomogram survival prediction models may aid in evaluating the prognosis of middle-aged and older patients with rectal adenocarcinoma and guiding the selection of the clinical treatment measures.

Indexed as

NomogramPrognostic modelRectum adenocarcinoma

Identifiers

PMID33186890
PMCPMC7658496
OpenAlexW3103669266

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.