Evidence map›Paper›PMID 39073708›Full record

ArticleDiscover oncology2024

Establishment of nomogram to predict overall survival and cancer-specific survival of local tumor resection in patients with colorectal cancer liver metastasis with unresectable metastases: a large population-based analysis.

Songlin Hou, Lifa Li, Huafang Hou, Tong Zhou, He Zhou

Abstract read
In one paragraph

Article in Discover oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Oncology letters · 2025
    Article
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

5 authors.

Songlin HouThe Second Department of Gastrointestinal Surgery, The Affiliated Hospital of North Sichuan Medical College, 1 Maoyuan South Road, Nanchong, 637000, Sichuan, People's Republic of China.
Lifa LiThe Second Department of Gastrointestinal Surgery, The Affiliated Hospital of North Sichuan Medical College, 1 Maoyuan South Road, Nanchong, 637000, Sichuan, People's Republic of China.
Huafang HouThe Second Department of Gastrointestinal Surgery, The Affiliated Hospital of North Sichuan Medical College, 1 Maoyuan South Road, Nanchong, 637000, Sichuan, People's Republic of China.
Tong ZhouThe Second Department of Gastrointestinal Surgery, The Affiliated Hospital of North Sichuan Medical College, 1 Maoyuan South Road, Nanchong, 637000, Sichuan, People's Republic of China.
He ZhouThe Second Department of Gastrointestinal Surgery, The Affiliated Hospital of North Sichuan Medical College, 1 Maoyuan South Road, Nanchong, 637000, Sichuan, People's Republic of China. zhouhe@nsmc.edu.cn.

Funding

the Free exploration project of applied basic research of science and technology department of Sichuan provinc 2021YJ0456the Scientific research development plan of North Sichuan Medical Colleg CBY20-QA-Y16the Scientific Research Project of Affiliated Hospital of North Sichuan Medical College 2021ZD001the Scientific Research Project of Affiliated Hospital of North Sichuan Medical College 2022JC001
6 · The paper itself

Abstract

background and purposeThe tumour-node metastasis (TNM) classification is a common model for evaluating the prognostic value of tumour patients. However, few models have been used to predict the survival outcomes of patients with colorectal cancer liver metastasis (CRLM) with unresectable metastases who received the primary local surgery. Thus, we utilized the Surveillance, Epidemiology, and End Results (SEER) database to establish novel nomograms for predicting the overall survival (OS) and cancer-specific survival (CSS) of these patients.

methodsExtracted primary data on CRLM patients by local surgery from SEER database. All prognostic factors of OS and CSS were determined by Cox regression analysis. The concordance index (C-index), receiver operating characteristic (ROC) curves and calibration curves were used to further evaluate the accuracy and discrimination of these nomograms. Decision curve analysis (DCA) was executed to evaluate the nomograms for the clinical net benefit. Risk stratification analysis (RSA) was used to evaluate the reliability of them in clinical.

results3622 eligible patients were screened and assigned to training cohort (1812) or validation cohort (1810). The age, chemotherapy, tumour grade, primary tumour site, tumour size, lymph node positive rate (LNR), marital status, and carcinoembryonic antigen (CEA) were independent prognostic factors of OS. Additionally, the age, chemotherapy, tumour grade, primary tumour site, tumour size, LNR, and CEA were independent prognostic factors of CSS. The results of C-indexes and ROC curves indicated that the established nomograms exhibited better discrimination power than TNM classification. The calibration curves demonstrated excellent agreement between the predicted and actual survival rates for 1-, 3-, and 5 year OS and CSS. Meanwhile, the validation cohort demonstrated similar results. Background the clinic context, the DCA showed that these nomograms have higher net benefits, and the RSA showed that patients were further divided into low risk, medium risk, and high risk groups according to the predicted scores from nomograms. And, the Kaplan-Meier curve and log-rank test showed that the survival differences among the three groups are statistically significant.

conclusionsThe prognostic nomograms showed very high accuracy, identifiability, and clinical practicality in predicting the OS and CSS of CRLM patients with unresectable metastases treated by local surgery at 1-, 3-, and 5 years, which might improve individualized predictions of survival risks and help clinicians formulate treatment plans.

Indexed as

Colorectal cancer liver metastasisLocal surgeryNomogramSEER

Identifiers

PMID39073708
PMCPMC11286894

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.