Evidence map›Paper›PMID 37720671›Full record

ArticleOncology letters2023

Establishment of a novel survival assessment and prediction model for advanced gastric cancer patients receiving immunotherapy.

Mingmin Sun, Yang Yang, Jun Zhao

Abstract read
In one paragraph

Article in Oncology letters, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–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

2 citing papers in PubMed.

  1. Article
  2. 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

3 authors.

Mingmin SunDepartment of Epidemiology and Statistics, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu 211166, P.R. China.
Yang YangDepartment of Oncology, Gulou Hospital, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, P.R. China.
Jun ZhaoAcademician Workstation, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, P.R. China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Currently, there are only a few risk assessment tools that provide predictions of survival duration for patients with gastric cancer (GC) receiving immunotherapy. The purpose of the present study was to develop and validate a nomogram that uses statistical data to predict survival and make risk assessments for patients with advanced staged GC. A total of 1,013 patients consisting of a development cohort (n=501) and validation cohort (n=512) collected during the time interval between January 2018 and June 2022 were included in the present study. The analysis consisted of the discrimination index, calibration plots and decision curve of the nomogram model. A total of 167 (33.33%) patients from the development cohort, and 158 (30.85%) from the validation cohort died during the observation period. The median overall survival (OS) of female patients was higher at 980 days (95% CI, 613-NA) compared with that of male patients, which was 748 days (95% CI, 597-NA; P=0.24). The median survival of patients with domestic immunotherapy was 789 (95% CI, 597-NA) days, which was lower compared with the imported immunotherapy group who had a median OS of 980 days (95% CI, 582-NA; P=0.22). A total of four independent predictors, age (HR=1.012; P=0.0245), histological grade (HR=1.395; P=0.016), immunotherapy cycles (HR=0.932; P=0.028) and line of first immunotherapy (HR=1.693; P=0.0003), were identified. The C-index was 0.64 and 0.67 for the development and validation cohorts, respectively. Patients who received more cycles of immunotherapy as the first-line treatment with highly differentiated tumor led to increase in the survival time of the patients. Thus, this nomogram could be used to determine the benefit of immunotherapies on patients at various stages of treatment of GC.

Indexed as

advanced gastric cancerdevelopment cohortprediction modelreceived immunotherapysurvival assessmentvalidation cohort

Identifiers

PMID37720671
PMCPMC10502925

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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.