Cargando…
A novel nomogram for identifying candidates for adjuvant chemotherapy in patients with stage IB gastric adenocarcinoma
BACKGROUND: The purpose of this research was to construct a novel predictive nomogram to identify specific stage IB gastric adenocarcinoma (GAC) populations who could benefit from postoperative adjuvant chemotherapy (ACT). METHOD: Between 2004 and 2015, 1889 stage IB GAC patients were extracted from...
Autores principales: | , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9987131/ https://www.ncbi.nlm.nih.gov/pubmed/36879203 http://dx.doi.org/10.1186/s12876-023-02706-6 |
_version_ | 1784901316695293952 |
---|---|
author | Xie, Yangyang Song, Xue Du, Danwei Jin, Haimin Li, Xiaowen Ni, Zhongkai Huang, Hai |
author_facet | Xie, Yangyang Song, Xue Du, Danwei Jin, Haimin Li, Xiaowen Ni, Zhongkai Huang, Hai |
author_sort | Xie, Yangyang |
collection | PubMed |
description | BACKGROUND: The purpose of this research was to construct a novel predictive nomogram to identify specific stage IB gastric adenocarcinoma (GAC) populations who could benefit from postoperative adjuvant chemotherapy (ACT). METHOD: Between 2004 and 2015, 1889 stage IB GAC patients were extracted from the Surveillance, Epidemiology, and End Results (SEER) program database. Then Kaplan–Meier survival analysis, univariate and multivariable Cox analyses, and univariate and multivariable logistic analyses were implemented. Finally, the predictive nomograms were constructed. The methods of area under the curve (AUC), calibration curve, and decision curve analysis (DCA) were used to validate the clinical effectiveness of the models. RESULTS: Of these patients, 708 cases underwent ACT, while the other 1181 patients didn’t receive ACT. After PSM, the patients in the ACT group presented a longer median overall survival (133 vs. 85 months, p = 0.0087). Among the ACT group, 194 (36.0%) patients achieving more prolonged overall survival than 85 months were regarded as the beneficiary population. Then the logistic regression analyses were performed, and age, gender, marital status, primary site, tumor size, and regional nodes examined were included as predicting factors to construct the nomogram. The AUC value was 0.725 in the training cohort and 0.739 in the validation cohort, which demonstrated good discrimination. And calibration curves indicated ideal consistency between the predicted and observed probabilities. Decision curve analysis presented a clinically useful model. Furthermore, the prognostic nomogram predicting 1-, 3-, and 5-year cancer-specific survival presented good predictive ability. CONCLUSION: The benefit nomogram could guide clinicians in decision-making and selecting optimal candidates for ACT among stage IB GAC patients. And the prognostic nomogram presented great prediction ability for these patients. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12876-023-02706-6. |
format | Online Article Text |
id | pubmed-9987131 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-99871312023-03-07 A novel nomogram for identifying candidates for adjuvant chemotherapy in patients with stage IB gastric adenocarcinoma Xie, Yangyang Song, Xue Du, Danwei Jin, Haimin Li, Xiaowen Ni, Zhongkai Huang, Hai BMC Gastroenterol Research BACKGROUND: The purpose of this research was to construct a novel predictive nomogram to identify specific stage IB gastric adenocarcinoma (GAC) populations who could benefit from postoperative adjuvant chemotherapy (ACT). METHOD: Between 2004 and 2015, 1889 stage IB GAC patients were extracted from the Surveillance, Epidemiology, and End Results (SEER) program database. Then Kaplan–Meier survival analysis, univariate and multivariable Cox analyses, and univariate and multivariable logistic analyses were implemented. Finally, the predictive nomograms were constructed. The methods of area under the curve (AUC), calibration curve, and decision curve analysis (DCA) were used to validate the clinical effectiveness of the models. RESULTS: Of these patients, 708 cases underwent ACT, while the other 1181 patients didn’t receive ACT. After PSM, the patients in the ACT group presented a longer median overall survival (133 vs. 85 months, p = 0.0087). Among the ACT group, 194 (36.0%) patients achieving more prolonged overall survival than 85 months were regarded as the beneficiary population. Then the logistic regression analyses were performed, and age, gender, marital status, primary site, tumor size, and regional nodes examined were included as predicting factors to construct the nomogram. The AUC value was 0.725 in the training cohort and 0.739 in the validation cohort, which demonstrated good discrimination. And calibration curves indicated ideal consistency between the predicted and observed probabilities. Decision curve analysis presented a clinically useful model. Furthermore, the prognostic nomogram predicting 1-, 3-, and 5-year cancer-specific survival presented good predictive ability. CONCLUSION: The benefit nomogram could guide clinicians in decision-making and selecting optimal candidates for ACT among stage IB GAC patients. And the prognostic nomogram presented great prediction ability for these patients. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12876-023-02706-6. BioMed Central 2023-03-06 /pmc/articles/PMC9987131/ /pubmed/36879203 http://dx.doi.org/10.1186/s12876-023-02706-6 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Xie, Yangyang Song, Xue Du, Danwei Jin, Haimin Li, Xiaowen Ni, Zhongkai Huang, Hai A novel nomogram for identifying candidates for adjuvant chemotherapy in patients with stage IB gastric adenocarcinoma |
title | A novel nomogram for identifying candidates for adjuvant chemotherapy in patients with stage IB gastric adenocarcinoma |
title_full | A novel nomogram for identifying candidates for adjuvant chemotherapy in patients with stage IB gastric adenocarcinoma |
title_fullStr | A novel nomogram for identifying candidates for adjuvant chemotherapy in patients with stage IB gastric adenocarcinoma |
title_full_unstemmed | A novel nomogram for identifying candidates for adjuvant chemotherapy in patients with stage IB gastric adenocarcinoma |
title_short | A novel nomogram for identifying candidates for adjuvant chemotherapy in patients with stage IB gastric adenocarcinoma |
title_sort | novel nomogram for identifying candidates for adjuvant chemotherapy in patients with stage ib gastric adenocarcinoma |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9987131/ https://www.ncbi.nlm.nih.gov/pubmed/36879203 http://dx.doi.org/10.1186/s12876-023-02706-6 |
work_keys_str_mv | AT xieyangyang anovelnomogramforidentifyingcandidatesforadjuvantchemotherapyinpatientswithstageibgastricadenocarcinoma AT songxue anovelnomogramforidentifyingcandidatesforadjuvantchemotherapyinpatientswithstageibgastricadenocarcinoma AT dudanwei anovelnomogramforidentifyingcandidatesforadjuvantchemotherapyinpatientswithstageibgastricadenocarcinoma AT jinhaimin anovelnomogramforidentifyingcandidatesforadjuvantchemotherapyinpatientswithstageibgastricadenocarcinoma AT lixiaowen anovelnomogramforidentifyingcandidatesforadjuvantchemotherapyinpatientswithstageibgastricadenocarcinoma AT nizhongkai anovelnomogramforidentifyingcandidatesforadjuvantchemotherapyinpatientswithstageibgastricadenocarcinoma AT huanghai anovelnomogramforidentifyingcandidatesforadjuvantchemotherapyinpatientswithstageibgastricadenocarcinoma AT xieyangyang novelnomogramforidentifyingcandidatesforadjuvantchemotherapyinpatientswithstageibgastricadenocarcinoma AT songxue novelnomogramforidentifyingcandidatesforadjuvantchemotherapyinpatientswithstageibgastricadenocarcinoma AT dudanwei novelnomogramforidentifyingcandidatesforadjuvantchemotherapyinpatientswithstageibgastricadenocarcinoma AT jinhaimin novelnomogramforidentifyingcandidatesforadjuvantchemotherapyinpatientswithstageibgastricadenocarcinoma AT lixiaowen novelnomogramforidentifyingcandidatesforadjuvantchemotherapyinpatientswithstageibgastricadenocarcinoma AT nizhongkai novelnomogramforidentifyingcandidatesforadjuvantchemotherapyinpatientswithstageibgastricadenocarcinoma AT huanghai novelnomogramforidentifyingcandidatesforadjuvantchemotherapyinpatientswithstageibgastricadenocarcinoma |