Risk prediction of second primary malignancies in patients after rectal cancer: analysis based on SEER Program.
Nomogram
Rectal cancer
Second primary malignancy
Seer
Treatment decision
Journal
BMC gastroenterology
ISSN: 1471-230X
Titre abrégé: BMC Gastroenterol
Pays: England
ID NLM: 100968547
Informations de publication
Date de publication:
12 Oct 2023
12 Oct 2023
Historique:
received:
15
06
2023
accepted:
26
09
2023
medline:
1
11
2023
pubmed:
13
10
2023
entrez:
12
10
2023
Statut:
epublish
Résumé
This study will focus on exploring the clinical characteristics of rectal cancer (RC) patients with Second Primary Malignancies (SPMs) and constructing a prognostic nomogram to provide clinical treatment decisions. We determined the association between risk factors and overall survival (OS) while establishing a nomogram to forecast the further OS status of these patients via Cox regression analysis. Finally, we evaluated the performance of the prognostic nomogram to predict further OS status. Nine parameters were identified to establish the prognostic nomogram in this study, and, the C-index of the training set and validation set was 0.691 (95%CI, 0.662-0.720) and 0.731 (95%CI, 0.676-0.786), respectively. The calibration curve showed a high agreement between the predicted and actual results, and the receiver operating characteristic (ROC) curves verified the superiority of our model for clinical usefulness. In addition, the nomogram classification could more precisely differentiate risk subgroups and improved the discrimination of SPMs' prognosis. We systematically explored the clinical characteristics of SPMs after RC and constructed a satisfactory nomogram.
Sections du résumé
BACKGROUND
BACKGROUND
This study will focus on exploring the clinical characteristics of rectal cancer (RC) patients with Second Primary Malignancies (SPMs) and constructing a prognostic nomogram to provide clinical treatment decisions.
METHODS
METHODS
We determined the association between risk factors and overall survival (OS) while establishing a nomogram to forecast the further OS status of these patients via Cox regression analysis. Finally, we evaluated the performance of the prognostic nomogram to predict further OS status.
RESULTS
RESULTS
Nine parameters were identified to establish the prognostic nomogram in this study, and, the C-index of the training set and validation set was 0.691 (95%CI, 0.662-0.720) and 0.731 (95%CI, 0.676-0.786), respectively. The calibration curve showed a high agreement between the predicted and actual results, and the receiver operating characteristic (ROC) curves verified the superiority of our model for clinical usefulness. In addition, the nomogram classification could more precisely differentiate risk subgroups and improved the discrimination of SPMs' prognosis.
CONCLUSIONS
CONCLUSIONS
We systematically explored the clinical characteristics of SPMs after RC and constructed a satisfactory nomogram.
Identifiants
pubmed: 37828423
doi: 10.1186/s12876-023-02974-2
pii: 10.1186/s12876-023-02974-2
pmc: PMC10568885
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
354Subventions
Organisme : National Natural Science Foundation of China
ID : 82002790
Organisme : National Natural Science Foundation of China
ID : 81902391
Organisme : National Natural Science Foundation of China
ID : 81902391
Informations de copyright
© 2023. BioMed Central Ltd., part of Springer Nature.
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