ArticleFrontiers in oncology2023
Prognostic risk factors and nomogram construction for sebaceous carcinoma: A population-based analysis.
Article in Frontiers in oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Sebaceous gland carcinoma (SGC) is a rare tumor for which there are currently no effective tools to predict patient outcomes. We analyzed the clinical and pathological prognostic risk factors of sebaceous carcinoma based on population data and created a nomogram of related risk factors, which can more accurately predict the 3-, 5-, and 10-year overall survival (OS) rates of patients. Methods: SGC patients between 2004 and 2015 were collected from the Surveillance, Epidemiology, and End Results (SEER) database and randomly assigned to training and validation cohorts. Relevant risk factors were identified by univariate and multivariate COX hazards regression methods and combined to produce a correlation nomogram. The concordance index (C-index), the area under the receiver operating characteristic (AUC) curve, and calibration plots have demonstrated the predictive power of the nomogram. Decision curve analysis (DCA) was used to measure nomograms in clinical practice. Results: A total of 2844 eligible patients were randomly assigned to 70% of the training group (n=1990) and 30% of the validation group (n=854) in this study. The derived meaningful prognostic factors were applied to the establishment of the nomogram. The C-index for OS was 0.725 (95% CI: 0.706-0.741) in the training cohort and 0.710 (95% CI: 0.683-0.737) in the validation cohort. The AUC and calibration plots of 3-, 5-, and 10-year OS rates showed that the nomogram had good predictive power. DCA demonstrated that the nomogram constructed in this study could provide a clinical net benefit. Conclusion: We created a novel nomogram of prognostic factors for SGC, which more accurately and comprehensively predicted 3-, 5-, and 10-year OS in SGC patients. This can help clinicians identify high-risk patients as early as possible, carry out personalized treatment, follow-up, and monitoring, and improve the survival rate of SGC 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.