Development and validation of prognostic prediction models for early-stage cervical cancer patients based on pathological intermediate-risk factors
Background: The combination patterns of pathological intermediate-risk factors and the choice of adjuvant therapy for early-stage cervical cancer (CC) remain controversial. Objectives: To develop and validate nomogram-based prediction models incorporating pathological intermediate-risk factors to pr...
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| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
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SAGE Publishing
2025-07-01
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| Series: | Therapeutic Advances in Medical Oncology |
| Online Access: | https://doi.org/10.1177/17588359251359461 |
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| _version_ | 1850067705267224576 |
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| author | Zihan Wang Ran Chu Namei Wu Ming Yuan Xiao Song Wei Tian Chunrun Yang Jipeng Wan Guoyun Wang |
| author_facet | Zihan Wang Ran Chu Namei Wu Ming Yuan Xiao Song Wei Tian Chunrun Yang Jipeng Wan Guoyun Wang |
| author_sort | Zihan Wang |
| collection | DOAJ |
| description | Background: The combination patterns of pathological intermediate-risk factors and the choice of adjuvant therapy for early-stage cervical cancer (CC) remain controversial. Objectives: To develop and validate nomogram-based prediction models incorporating pathological intermediate-risk factors to predict survival outcomes and optimize adjuvant therapy strategies in early-stage CC patients. Design: A multicenter retrospective study. Methods: A total of 1104 patients with stage IB-IIA CC who underwent primary surgical treatment and had no pathological high-risk factors were retrospectively enrolled from three tertiary medical centers in China between January 2005 and December 2017. Patients were randomly assigned to development and validation cohorts (approximately 3:1 ratio). Prognostic models for disease-free survival (DFS) and overall survival (OS) were developed by Cox proportional hazards regression and visualized using nomograms. Results: In this study, four prognostic models were developed incorporating different combinations of five key variables: lymphovascular space involvement (LVSI), stromal invasion (SI), tumor size (TS), histological type, and adjuvant therapy. Among these, Model 4 (LVSI + SI + TS + histological type + adjuvant therapy) demonstrated the highest discriminatory performance, with C-indices of 0.79 for both DFS and OS in the development cohort, and 0.84 for DFS and 0.77 for OS in the validation cohort. Model 4 also effectively stratified patients into prognostic risk groups in both cohorts, with high-risk patients exhibiting significantly worse DFS (development cohort: p < 0.0001; validation cohort: p = 0.0011) and OS (development cohort: p < 0.0001; validation cohort: p = 0.0036) compared to low-risk patients. Conclusion: The nomogram models developed in this study may provide individualized prognostic predictions for early-stage CC patients, potentially facilitating personalized decision-making regarding adjuvant therapy, though further validation in diverse patient cohorts and prospective studies is needed. |
| format | Article |
| id | doaj-art-9a36cb9160bd468c8e31e25d291ee974 |
| institution | DOAJ |
| issn | 1758-8359 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | SAGE Publishing |
| record_format | Article |
| series | Therapeutic Advances in Medical Oncology |
| spelling | doaj-art-9a36cb9160bd468c8e31e25d291ee9742025-08-20T02:48:13ZengSAGE PublishingTherapeutic Advances in Medical Oncology1758-83592025-07-011710.1177/17588359251359461Development and validation of prognostic prediction models for early-stage cervical cancer patients based on pathological intermediate-risk factorsZihan WangRan ChuNamei WuMing YuanXiao SongWei TianChunrun YangJipeng WanGuoyun WangBackground: The combination patterns of pathological intermediate-risk factors and the choice of adjuvant therapy for early-stage cervical cancer (CC) remain controversial. Objectives: To develop and validate nomogram-based prediction models incorporating pathological intermediate-risk factors to predict survival outcomes and optimize adjuvant therapy strategies in early-stage CC patients. Design: A multicenter retrospective study. Methods: A total of 1104 patients with stage IB-IIA CC who underwent primary surgical treatment and had no pathological high-risk factors were retrospectively enrolled from three tertiary medical centers in China between January 2005 and December 2017. Patients were randomly assigned to development and validation cohorts (approximately 3:1 ratio). Prognostic models for disease-free survival (DFS) and overall survival (OS) were developed by Cox proportional hazards regression and visualized using nomograms. Results: In this study, four prognostic models were developed incorporating different combinations of five key variables: lymphovascular space involvement (LVSI), stromal invasion (SI), tumor size (TS), histological type, and adjuvant therapy. Among these, Model 4 (LVSI + SI + TS + histological type + adjuvant therapy) demonstrated the highest discriminatory performance, with C-indices of 0.79 for both DFS and OS in the development cohort, and 0.84 for DFS and 0.77 for OS in the validation cohort. Model 4 also effectively stratified patients into prognostic risk groups in both cohorts, with high-risk patients exhibiting significantly worse DFS (development cohort: p < 0.0001; validation cohort: p = 0.0011) and OS (development cohort: p < 0.0001; validation cohort: p = 0.0036) compared to low-risk patients. Conclusion: The nomogram models developed in this study may provide individualized prognostic predictions for early-stage CC patients, potentially facilitating personalized decision-making regarding adjuvant therapy, though further validation in diverse patient cohorts and prospective studies is needed.https://doi.org/10.1177/17588359251359461 |
| spellingShingle | Zihan Wang Ran Chu Namei Wu Ming Yuan Xiao Song Wei Tian Chunrun Yang Jipeng Wan Guoyun Wang Development and validation of prognostic prediction models for early-stage cervical cancer patients based on pathological intermediate-risk factors Therapeutic Advances in Medical Oncology |
| title | Development and validation of prognostic prediction models for early-stage cervical cancer patients based on pathological intermediate-risk factors |
| title_full | Development and validation of prognostic prediction models for early-stage cervical cancer patients based on pathological intermediate-risk factors |
| title_fullStr | Development and validation of prognostic prediction models for early-stage cervical cancer patients based on pathological intermediate-risk factors |
| title_full_unstemmed | Development and validation of prognostic prediction models for early-stage cervical cancer patients based on pathological intermediate-risk factors |
| title_short | Development and validation of prognostic prediction models for early-stage cervical cancer patients based on pathological intermediate-risk factors |
| title_sort | development and validation of prognostic prediction models for early stage cervical cancer patients based on pathological intermediate risk factors |
| url | https://doi.org/10.1177/17588359251359461 |
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