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A non-lab nomogram of survival prediction in home hospice care patients with gastrointestinal cancer
BACKGROUND: Patients suffering from gastrointestinal cancer comprise a large group receiving home hospice care in China, however, little is known about the prediction of their survival time. This study aimed to develop a gastrointestinal cancer-specific non-lab nomogram predicting survival time in h...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7722330/ https://www.ncbi.nlm.nih.gov/pubmed/33287827 http://dx.doi.org/10.1186/s12904-020-00690-2 |
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author | Wang, Muqing Jing, Xubin Cao, Weihua Zeng, Yicheng Wu, Chaofen Zeng, Weilong Chen, Wenxia Hu, Xi Zhou, Yanna Cai, Xianbin |
author_facet | Wang, Muqing Jing, Xubin Cao, Weihua Zeng, Yicheng Wu, Chaofen Zeng, Weilong Chen, Wenxia Hu, Xi Zhou, Yanna Cai, Xianbin |
author_sort | Wang, Muqing |
collection | PubMed |
description | BACKGROUND: Patients suffering from gastrointestinal cancer comprise a large group receiving home hospice care in China, however, little is known about the prediction of their survival time. This study aimed to develop a gastrointestinal cancer-specific non-lab nomogram predicting survival time in home-based hospice. METHODS: We retrospectively studied the patients with gastrointestinal cancer from a home-based hospice between 2008 and 2018. General baseline characteristics, disease-related characteristics, and related assessment scale scores were collected from the case records. The data were randomly split into a training set (75%) for developing a predictive nomogram and a testing set (25%) for validation. A non-lab nomogram predicting the 30-day and 60-day survival probability was created using the least absolute shrinkage and selection operator (LASSO) Cox regression. We evaluated the performance of our predictive model by means of the area under receiver operating characteristic curve (AUC) and calibration curve. RESULTS: A total of 1618 patients were included and divided into two sets: 1214 patients (110 censored) as training dataset and 404 patients (33 censored) as testing dataset. The median survival time for overall included patients was 35 days (IQR, 17–66). The 5 most significant prognostic variables were identified to construct the nomogram among all 28 initial variables, including Karnofsky Performance Status (KPS), abdominal distention, edema, quality of life (QOL), and duration of pain. In training dataset validation, the AUC at 30 days and 60 days were 0.723 (95% CI, 0.694–0.753) and 0.733 (95% CI, 0.702–0.763), respectively. Similarly, the AUC value was 0.724 (0.673–0.774) at 30 days and 0.725 (0.672–0.778) at 60 days in the testing dataset validation. Further, the calibration curves revealed good agreement between the nomogram predictions and actual observations in both the training and testing dataset. CONCLUSION: This non-lab nomogram may be a useful clinical tool. It needs prospective multicenter validation as well as testing with Chinese clinicians in charge of hospice patients with gastrointestinal cancer to assess acceptability and usability. |
format | Online Article Text |
id | pubmed-7722330 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-77223302020-12-08 A non-lab nomogram of survival prediction in home hospice care patients with gastrointestinal cancer Wang, Muqing Jing, Xubin Cao, Weihua Zeng, Yicheng Wu, Chaofen Zeng, Weilong Chen, Wenxia Hu, Xi Zhou, Yanna Cai, Xianbin BMC Palliat Care Research Article BACKGROUND: Patients suffering from gastrointestinal cancer comprise a large group receiving home hospice care in China, however, little is known about the prediction of their survival time. This study aimed to develop a gastrointestinal cancer-specific non-lab nomogram predicting survival time in home-based hospice. METHODS: We retrospectively studied the patients with gastrointestinal cancer from a home-based hospice between 2008 and 2018. General baseline characteristics, disease-related characteristics, and related assessment scale scores were collected from the case records. The data were randomly split into a training set (75%) for developing a predictive nomogram and a testing set (25%) for validation. A non-lab nomogram predicting the 30-day and 60-day survival probability was created using the least absolute shrinkage and selection operator (LASSO) Cox regression. We evaluated the performance of our predictive model by means of the area under receiver operating characteristic curve (AUC) and calibration curve. RESULTS: A total of 1618 patients were included and divided into two sets: 1214 patients (110 censored) as training dataset and 404 patients (33 censored) as testing dataset. The median survival time for overall included patients was 35 days (IQR, 17–66). The 5 most significant prognostic variables were identified to construct the nomogram among all 28 initial variables, including Karnofsky Performance Status (KPS), abdominal distention, edema, quality of life (QOL), and duration of pain. In training dataset validation, the AUC at 30 days and 60 days were 0.723 (95% CI, 0.694–0.753) and 0.733 (95% CI, 0.702–0.763), respectively. Similarly, the AUC value was 0.724 (0.673–0.774) at 30 days and 0.725 (0.672–0.778) at 60 days in the testing dataset validation. Further, the calibration curves revealed good agreement between the nomogram predictions and actual observations in both the training and testing dataset. CONCLUSION: This non-lab nomogram may be a useful clinical tool. It needs prospective multicenter validation as well as testing with Chinese clinicians in charge of hospice patients with gastrointestinal cancer to assess acceptability and usability. BioMed Central 2020-12-07 /pmc/articles/PMC7722330/ /pubmed/33287827 http://dx.doi.org/10.1186/s12904-020-00690-2 Text en © The Author(s) 2020 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/. The Creative Commons Public Domain Dedication waiver (http://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 Article Wang, Muqing Jing, Xubin Cao, Weihua Zeng, Yicheng Wu, Chaofen Zeng, Weilong Chen, Wenxia Hu, Xi Zhou, Yanna Cai, Xianbin A non-lab nomogram of survival prediction in home hospice care patients with gastrointestinal cancer |
title | A non-lab nomogram of survival prediction in home hospice care patients with gastrointestinal cancer |
title_full | A non-lab nomogram of survival prediction in home hospice care patients with gastrointestinal cancer |
title_fullStr | A non-lab nomogram of survival prediction in home hospice care patients with gastrointestinal cancer |
title_full_unstemmed | A non-lab nomogram of survival prediction in home hospice care patients with gastrointestinal cancer |
title_short | A non-lab nomogram of survival prediction in home hospice care patients with gastrointestinal cancer |
title_sort | non-lab nomogram of survival prediction in home hospice care patients with gastrointestinal cancer |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7722330/ https://www.ncbi.nlm.nih.gov/pubmed/33287827 http://dx.doi.org/10.1186/s12904-020-00690-2 |
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