External validation and adaptation of a dynamic prediction model for patients with high-grade extremity soft tissue sarcoma.
dynamic prediction
external validation
landmark analysis
soft tissue sarcoma
survival
Journal
Journal of surgical oncology
ISSN: 1096-9098
Titre abrégé: J Surg Oncol
Pays: United States
ID NLM: 0222643
Informations de publication
Date de publication:
Mar 2021
Mar 2021
Historique:
received:
16
10
2020
revised:
16
10
2020
accepted:
30
11
2020
pubmed:
18
12
2020
medline:
11
3
2021
entrez:
17
12
2020
Statut:
ppublish
Résumé
A dynamic prediction model for patients with soft tissue sarcoma of the extremities was previously developed to predict updated overall survival probabilities throughout patient follow-up. This study updates and externally validates the dynamic model. Data from 3826 patients with high-grade extremity soft tissue sarcoma, treated surgically with curative intent were used to update the dynamic PERsonalised SARcoma Care (PERSARC) model. Patients were added to the model development cohort and grade was included in the model. External validation was performed with data from 1111 patients treated at a single tertiary center. Calibration plots show good model calibration. Dynamic C-indices suggest that the model can discriminate between high- and low-risk patients. The dynamic C-indices at 0, 1, 2, 3, 4, and 5 years after surgery were equal to 0.697, 0.790, 0.822, 0.818, 0.812, and 0.827, respectively. Results from the external validation show that the dynamic PERSARC model is reliable in predicting the probability of surviving an additional 5 years from a specific prediction time point during follow-up. The model combines patient-, treatment-specific and time-dependent variables such as local recurrence and distant metastasis to provide accurate survival predictions throughout follow-up and is available through the PERSARC app.
Sections du résumé
BACKGROUND AND OBJECTIVES
OBJECTIVE
A dynamic prediction model for patients with soft tissue sarcoma of the extremities was previously developed to predict updated overall survival probabilities throughout patient follow-up. This study updates and externally validates the dynamic model.
METHODS
METHODS
Data from 3826 patients with high-grade extremity soft tissue sarcoma, treated surgically with curative intent were used to update the dynamic PERsonalised SARcoma Care (PERSARC) model. Patients were added to the model development cohort and grade was included in the model. External validation was performed with data from 1111 patients treated at a single tertiary center.
RESULTS
RESULTS
Calibration plots show good model calibration. Dynamic C-indices suggest that the model can discriminate between high- and low-risk patients. The dynamic C-indices at 0, 1, 2, 3, 4, and 5 years after surgery were equal to 0.697, 0.790, 0.822, 0.818, 0.812, and 0.827, respectively.
CONCLUSION
CONCLUSIONS
Results from the external validation show that the dynamic PERSARC model is reliable in predicting the probability of surviving an additional 5 years from a specific prediction time point during follow-up. The model combines patient-, treatment-specific and time-dependent variables such as local recurrence and distant metastasis to provide accurate survival predictions throughout follow-up and is available through the PERSARC app.
Identifiants
pubmed: 33332599
doi: 10.1002/jso.26337
pmc: PMC7985864
doi:
Types de publication
Journal Article
Validation Study
Langues
eng
Sous-ensembles de citation
IM
Pagination
1050-1056Subventions
Organisme : KWF Kankerbestrijding
ID : UL2015-8028
Informations de copyright
© 2020 The Authors. Journal of Surgical Oncology Published by Wiley Periodicals LLC.
Références
Cancer. 2005 Jan 15;103(2):402-8
pubmed: 15578681
Control Clin Trials. 1996 Aug;17(4):343-6
pubmed: 8889347
Eur J Cancer. 2017 Sep;83:313-323
pubmed: 28797949
J Clin Oncol. 2018 Mar 1;36(7):704-709
pubmed: 29346043
Surg Oncol. 2018 Dec;27(4):695-701
pubmed: 30449495
Int J Cancer. 1984 Jan 15;33(1):37-42
pubmed: 6693192
Eur J Cancer. 2018 Dec;105:19-27
pubmed: 30384013
J Surg Oncol. 2021 Mar;123(4):1050-1056
pubmed: 33332599
Lancet Oncol. 2016 May;17(5):671-80
pubmed: 27068860
Acta Paediatr. 2007 May;96(5):644-7
pubmed: 17376185
Ann Intern Med. 2015 Jan 6;162(1):55-63
pubmed: 25560714
Eur J Cancer. 2019 Mar;109:51-60
pubmed: 30690293
Eur J Cancer. 2018 Apr;93:28-36
pubmed: 29475197
Ann Surg. 2012 Feb;255(2):343-7
pubmed: 22143203