ArticleJournal of cancer research and clinical oncology2023
Developing prognostic nomograms to predict overall survival and cancer-specific survival in synchronous multiple primary colorectal cancer based on the SEER database.
Article in Journal of cancer research and clinical oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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.
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.
Who cites it
2 citing papers in PubMed, 3 citations in OpenAlex.
- Nomogram Development for Predicting Synchronous Lung Metastasis in Patients with T1 Colorectal Cancer: An SEER-Based Analysis.Medicina (Kaunas, Lithuania) · 2026Article
- Development and validation of comprehensive nomograms from the SEER database for predicting early mortality in metastatic rectal cancer patients.BMC gastroenterology · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundSynchronous multiple primary colorectal cancer (SMPCC) is a rare subtype of CRC, characterized by the presence of two or more primary CRC lesions simultaneously or within 6 months from the detection of the first lesion. We aim to develop a novel nomogram to predict OS and CSS for SMPCC patients using data from the SEER database.
methodsThe clinical variables and survival data of SMPCC patients between 2004 and 2018 were retrieved from the Surveillance, Epidemiology, and End Results (SEER) database. Appropriate inclusion and exclusion criteria were established to screen the enrolled patients. Univariate and multivariate Cox regression analyses were used to identify the independent risk factors for OS and CSS. The performance of the nomogram was evaluated using the concordance index (C-index), calibration curves, and the area under the curve (AUC) of a receiver operating characteristics curve (ROC). A decision curve analysis (DCA) was generated to compare the net benefits of the nomogram with those of the TNM staging system.
resultsA total of 6772 SMPCC patients were enrolled in the study and randomly assigned to the training (n = 4670) and validation (n = 2002) cohorts. Multivariate Cox analysis confirmed that race, marital status, age, histology, tumor position, T stage, N stage, M stage, chemotherapy, and the number of dissected LNs were independent prognostic factors.The C-index values for OS and CSS prediction were 0.716 (95% CI 0.705-0.727) and 0.718 (95% CI 0.702-0.734) in the training cohort, and 0.760 (95% CI 0.747-0.773) and 0.749 (95% CI 0.728-0.769) in the validation cohort. The ROC and calibration curves indicated that the model had good stability and reliability. Decision curve analysis revealed that the nomograms provided a more significant clinical net benefit than the TNM staging system.
conclusionWe developed a novel nomogram for clinicians to predict OS and CSS, which could be used to optimize the treatment in SMPCC patients.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.