Development and Validation of a DeepSurv Nomogram to Predict Survival Outcomes and Guide Personalized Adjuvant Chemotherapy in Non-Small Cell Lung Cancer
ObjectiveTo develop and validate a DeepSurv nomogram based on radiomic features extracted from computed tomography images and clinicopathological factors, to predict the overall survival and guide individualized adjuvant chemotherapy in patients with non-small cell lung cancer (NSCLC).Patients and M...
| Main Authors: | , , , , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2022-06-01
|
| Series: | Frontiers in Oncology |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fonc.2022.895014/full |
| _version_ | 1818256136612085760 |
|---|---|
| author | Bin Yang Bin Yang Chengxing Liu Ren Wu Jing Zhong Ang Li Lu Ma Jian Zhong Saisai Yin Changsheng Zhou Yingqian Ge Xinwei Tao Longjiang Zhang Guangming Lu Guangming Lu |
| author_facet | Bin Yang Bin Yang Chengxing Liu Ren Wu Jing Zhong Ang Li Lu Ma Jian Zhong Saisai Yin Changsheng Zhou Yingqian Ge Xinwei Tao Longjiang Zhang Guangming Lu Guangming Lu |
| author_sort | Bin Yang |
| collection | DOAJ |
| description | ObjectiveTo develop and validate a DeepSurv nomogram based on radiomic features extracted from computed tomography images and clinicopathological factors, to predict the overall survival and guide individualized adjuvant chemotherapy in patients with non-small cell lung cancer (NSCLC).Patients and MethodsThis retrospective study involved 976 consecutive patients with NSCLC (training cohort, n=683; validation cohort, n=293). DeepSurv was constructed based on 1,227 radiomic features, and the risk score was calculated for each patient as the output. A clinical multivariate Cox regression model was built with clinicopathological factors to determine the independent risk factors. Finally, a DeepSurv nomogram was constructed by integrating the risk score and independent clinicopathological factors. The discrimination capability, calibration, and clinical usefulness of the nomogram performance were assessed using concordance index evaluation, the Greenwood-Nam-D’Agostino test, and decision curve analysis, respectively. The treatment strategy was analyzed using a Kaplan–Meier curve and log-rank test for the high- and low-risk groups.ResultsThe DeepSurv nomogram yielded a significantly better concordance index (training cohort, 0.821; validation cohort 0.768) with goodness-of-fit (P<0.05). The risk score, age, thyroid transcription factor-1, Ki-67, and disease stage were the independent risk factors for NSCLC.The Greenwood-Nam-D’Agostino test showed good calibration performance (P=0.39). Both high- and low-risk patients did not benefit from adjuvant chemotherapy, and chemotherapy in low-risk groups may lead to a poorer prognosis.ConclusionsThe DeepSurv nomogram, which is based on the risk score and independent risk factors, had good predictive performance for survival outcome. Further, it could be used to guide personalized adjuvant chemotherapy in patients with NSCLC. |
| first_indexed | 2024-12-12T17:22:58Z |
| format | Article |
| id | doaj.art-ec3093a9be5d4d63b089d6bd6cacc6f8 |
| institution | Directory Open Access Journal |
| issn | 2234-943X |
| language | English |
| last_indexed | 2024-12-12T17:22:58Z |
| publishDate | 2022-06-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Oncology |
| spelling | doaj.art-ec3093a9be5d4d63b089d6bd6cacc6f82022-12-22T00:17:35ZengFrontiers Media S.A.Frontiers in Oncology2234-943X2022-06-011210.3389/fonc.2022.895014895014Development and Validation of a DeepSurv Nomogram to Predict Survival Outcomes and Guide Personalized Adjuvant Chemotherapy in Non-Small Cell Lung CancerBin Yang0Bin Yang1Chengxing Liu2Ren Wu3Jing Zhong4Ang Li5Lu Ma6Jian Zhong7Saisai Yin8Changsheng Zhou9Yingqian Ge10Xinwei Tao11Longjiang Zhang12Guangming Lu13Guangming Lu14Medical Imaging Center, Calmette Hospital and The First Hospital of Kunming (Affiliated Calmette Hospital of Kunming Medical University), Kunming, ChinaDepartment of Medical Imaging, Affiliated Jinling Hospital, Medical School of Nanjing University, Nanjing, ChinaDepartment of Cardiology, Tongji Hospital, Tongji University School of Medicine, Shanghai, ChinaDepartment of Medical Imaging, Jinling Hospital, Nanjing Medical University, Nanjing, ChinaDepartment of Medical Imaging, Affiliated Jinling Hospital, Medical School of Nanjing University, Nanjing, ChinaDepartment of Medical Imaging, Affiliated Jinling Hospital, Medical School of Nanjing University, Nanjing, ChinaDepartment of Medical Imaging, Affiliated Jinling Hospital, Medical School of Nanjing University, Nanjing, ChinaDepartment of Medical Imaging, Affiliated Jinling Hospital, Medical School of Nanjing University, Nanjing, ChinaDepartment of Medical Imaging, Affiliated Jinling Hospital, Medical School of Nanjing University, Nanjing, ChinaDepartment of Medical Imaging, Affiliated Jinling Hospital, Medical School of Nanjing University, Nanjing, ChinaSiemens Healthineers Ltd., Shanghai, ChinaSiemens Healthineers Ltd., Shanghai, ChinaDepartment of Medical Imaging, Affiliated Jinling Hospital, Medical School of Nanjing University, Nanjing, ChinaDepartment of Medical Imaging, Affiliated Jinling Hospital, Medical School of Nanjing University, Nanjing, ChinaDepartment of Medical Imaging, Jinling Hospital, Nanjing Medical University, Nanjing, ChinaObjectiveTo develop and validate a DeepSurv nomogram based on radiomic features extracted from computed tomography images and clinicopathological factors, to predict the overall survival and guide individualized adjuvant chemotherapy in patients with non-small cell lung cancer (NSCLC).Patients and MethodsThis retrospective study involved 976 consecutive patients with NSCLC (training cohort, n=683; validation cohort, n=293). DeepSurv was constructed based on 1,227 radiomic features, and the risk score was calculated for each patient as the output. A clinical multivariate Cox regression model was built with clinicopathological factors to determine the independent risk factors. Finally, a DeepSurv nomogram was constructed by integrating the risk score and independent clinicopathological factors. The discrimination capability, calibration, and clinical usefulness of the nomogram performance were assessed using concordance index evaluation, the Greenwood-Nam-D’Agostino test, and decision curve analysis, respectively. The treatment strategy was analyzed using a Kaplan–Meier curve and log-rank test for the high- and low-risk groups.ResultsThe DeepSurv nomogram yielded a significantly better concordance index (training cohort, 0.821; validation cohort 0.768) with goodness-of-fit (P<0.05). The risk score, age, thyroid transcription factor-1, Ki-67, and disease stage were the independent risk factors for NSCLC.The Greenwood-Nam-D’Agostino test showed good calibration performance (P=0.39). Both high- and low-risk patients did not benefit from adjuvant chemotherapy, and chemotherapy in low-risk groups may lead to a poorer prognosis.ConclusionsThe DeepSurv nomogram, which is based on the risk score and independent risk factors, had good predictive performance for survival outcome. Further, it could be used to guide personalized adjuvant chemotherapy in patients with NSCLC.https://www.frontiersin.org/articles/10.3389/fonc.2022.895014/fullchemotherapyDeepSurvnon-small cell lung cancersurvival outcomeradiomics |
| spellingShingle | Bin Yang Bin Yang Chengxing Liu Ren Wu Jing Zhong Ang Li Lu Ma Jian Zhong Saisai Yin Changsheng Zhou Yingqian Ge Xinwei Tao Longjiang Zhang Guangming Lu Guangming Lu Development and Validation of a DeepSurv Nomogram to Predict Survival Outcomes and Guide Personalized Adjuvant Chemotherapy in Non-Small Cell Lung Cancer Frontiers in Oncology chemotherapy DeepSurv non-small cell lung cancer survival outcome radiomics |
| title | Development and Validation of a DeepSurv Nomogram to Predict Survival Outcomes and Guide Personalized Adjuvant Chemotherapy in Non-Small Cell Lung Cancer |
| title_full | Development and Validation of a DeepSurv Nomogram to Predict Survival Outcomes and Guide Personalized Adjuvant Chemotherapy in Non-Small Cell Lung Cancer |
| title_fullStr | Development and Validation of a DeepSurv Nomogram to Predict Survival Outcomes and Guide Personalized Adjuvant Chemotherapy in Non-Small Cell Lung Cancer |
| title_full_unstemmed | Development and Validation of a DeepSurv Nomogram to Predict Survival Outcomes and Guide Personalized Adjuvant Chemotherapy in Non-Small Cell Lung Cancer |
| title_short | Development and Validation of a DeepSurv Nomogram to Predict Survival Outcomes and Guide Personalized Adjuvant Chemotherapy in Non-Small Cell Lung Cancer |
| title_sort | development and validation of a deepsurv nomogram to predict survival outcomes and guide personalized adjuvant chemotherapy in non small cell lung cancer |
| topic | chemotherapy DeepSurv non-small cell lung cancer survival outcome radiomics |
| url | https://www.frontiersin.org/articles/10.3389/fonc.2022.895014/full |
| work_keys_str_mv | AT binyang developmentandvalidationofadeepsurvnomogramtopredictsurvivaloutcomesandguidepersonalizedadjuvantchemotherapyinnonsmallcelllungcancer AT binyang developmentandvalidationofadeepsurvnomogramtopredictsurvivaloutcomesandguidepersonalizedadjuvantchemotherapyinnonsmallcelllungcancer AT chengxingliu developmentandvalidationofadeepsurvnomogramtopredictsurvivaloutcomesandguidepersonalizedadjuvantchemotherapyinnonsmallcelllungcancer AT renwu developmentandvalidationofadeepsurvnomogramtopredictsurvivaloutcomesandguidepersonalizedadjuvantchemotherapyinnonsmallcelllungcancer AT jingzhong developmentandvalidationofadeepsurvnomogramtopredictsurvivaloutcomesandguidepersonalizedadjuvantchemotherapyinnonsmallcelllungcancer AT angli developmentandvalidationofadeepsurvnomogramtopredictsurvivaloutcomesandguidepersonalizedadjuvantchemotherapyinnonsmallcelllungcancer AT luma developmentandvalidationofadeepsurvnomogramtopredictsurvivaloutcomesandguidepersonalizedadjuvantchemotherapyinnonsmallcelllungcancer AT jianzhong developmentandvalidationofadeepsurvnomogramtopredictsurvivaloutcomesandguidepersonalizedadjuvantchemotherapyinnonsmallcelllungcancer AT saisaiyin developmentandvalidationofadeepsurvnomogramtopredictsurvivaloutcomesandguidepersonalizedadjuvantchemotherapyinnonsmallcelllungcancer AT changshengzhou developmentandvalidationofadeepsurvnomogramtopredictsurvivaloutcomesandguidepersonalizedadjuvantchemotherapyinnonsmallcelllungcancer AT yingqiange developmentandvalidationofadeepsurvnomogramtopredictsurvivaloutcomesandguidepersonalizedadjuvantchemotherapyinnonsmallcelllungcancer AT xinweitao developmentandvalidationofadeepsurvnomogramtopredictsurvivaloutcomesandguidepersonalizedadjuvantchemotherapyinnonsmallcelllungcancer AT longjiangzhang developmentandvalidationofadeepsurvnomogramtopredictsurvivaloutcomesandguidepersonalizedadjuvantchemotherapyinnonsmallcelllungcancer AT guangminglu developmentandvalidationofadeepsurvnomogramtopredictsurvivaloutcomesandguidepersonalizedadjuvantchemotherapyinnonsmallcelllungcancer AT guangminglu developmentandvalidationofadeepsurvnomogramtopredictsurvivaloutcomesandguidepersonalizedadjuvantchemotherapyinnonsmallcelllungcancer |