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Ordinal logistic regression model describing factors associated with extent of nodal involvement in oral cancer patients and its prospective validation

BACKGROUND: Oral cancer is the most common cancer among Indian men, and has strong tendency of metastatic spread to neck lymph node which strongly influences prognosis especially 5 year survival-rate and also guides the related managements more effectively. Therefore, a reliable and accurate means o...

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Autores principales: Singh, Vishwajeet, Dwivedi, Sada Nand, Deo, S. V. S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7183690/
https://www.ncbi.nlm.nih.gov/pubmed/32336269
http://dx.doi.org/10.1186/s12874-020-00985-1
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author Singh, Vishwajeet
Dwivedi, Sada Nand
Deo, S. V. S.
author_facet Singh, Vishwajeet
Dwivedi, Sada Nand
Deo, S. V. S.
author_sort Singh, Vishwajeet
collection PubMed
description BACKGROUND: Oral cancer is the most common cancer among Indian men, and has strong tendency of metastatic spread to neck lymph node which strongly influences prognosis especially 5 year survival-rate and also guides the related managements more effectively. Therefore, a reliable and accurate means of preoperative evaluation of extent of nodal involvement becomes crucial. However, earlier researchers have preferred to address mainly its dichotomous form (involved/not-involved) instead of ordinal form while dealing with epidemiology of nodal involvement. As a matter of fact, consideration of ordinal form appropriately may increase not only the efficiency of the developed model but also accuracy in the results and related implications. Hence, to develop a model describing factors associated with ordinal form of nodal involvement was major focus of this study. METHODS: The data for model building were taken from the Department of Surgical Oncology, Dr.BRA-IRCH, AIIMS, New Delhi, India. All the OSCC patients (duly operated including neck dissection) and confirmed histopathologically from 1995 to 2013 were included. Further, another data of 204 patients collected prospectively from 2014 to 2015 was considered for the validation of the developed model. To assess the factors associated with extent of nodal involvement, as a first attempt in the field of OSCC, stepwise multivariable regression procedure was used and results are presented as odds-ratio and corresponding 95% confidence interval (CI). For appropriate accounting of ordinal form, the ordinal models were assessed and compared. Also, performance of the developed model was validated on a prospectively collected another data. RESULTS: Under multivariable proportional odds model, pain at the time of presentation, sub mucous fibrosis, palpable neck node, oral site and degree of differentiation were found to be significantly associated factors with extent of nodal involvement. In addition, tumor size also emerged to be significant under partial-proportional odds model. CONCLUSIONS: The analytical results under the present study reveal that in case of ordinal form of the outcome, appropriate ordinal regression may be a preferred choice. Present data suggest that, pain, sub mucous fibrosis, palpable neck node, oral site, degree of differentiation and tumor size are the most probable associated factors with extent of nodal involvement.
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spelling pubmed-71836902020-04-29 Ordinal logistic regression model describing factors associated with extent of nodal involvement in oral cancer patients and its prospective validation Singh, Vishwajeet Dwivedi, Sada Nand Deo, S. V. S. BMC Med Res Methodol Research Article BACKGROUND: Oral cancer is the most common cancer among Indian men, and has strong tendency of metastatic spread to neck lymph node which strongly influences prognosis especially 5 year survival-rate and also guides the related managements more effectively. Therefore, a reliable and accurate means of preoperative evaluation of extent of nodal involvement becomes crucial. However, earlier researchers have preferred to address mainly its dichotomous form (involved/not-involved) instead of ordinal form while dealing with epidemiology of nodal involvement. As a matter of fact, consideration of ordinal form appropriately may increase not only the efficiency of the developed model but also accuracy in the results and related implications. Hence, to develop a model describing factors associated with ordinal form of nodal involvement was major focus of this study. METHODS: The data for model building were taken from the Department of Surgical Oncology, Dr.BRA-IRCH, AIIMS, New Delhi, India. All the OSCC patients (duly operated including neck dissection) and confirmed histopathologically from 1995 to 2013 were included. Further, another data of 204 patients collected prospectively from 2014 to 2015 was considered for the validation of the developed model. To assess the factors associated with extent of nodal involvement, as a first attempt in the field of OSCC, stepwise multivariable regression procedure was used and results are presented as odds-ratio and corresponding 95% confidence interval (CI). For appropriate accounting of ordinal form, the ordinal models were assessed and compared. Also, performance of the developed model was validated on a prospectively collected another data. RESULTS: Under multivariable proportional odds model, pain at the time of presentation, sub mucous fibrosis, palpable neck node, oral site and degree of differentiation were found to be significantly associated factors with extent of nodal involvement. In addition, tumor size also emerged to be significant under partial-proportional odds model. CONCLUSIONS: The analytical results under the present study reveal that in case of ordinal form of the outcome, appropriate ordinal regression may be a preferred choice. Present data suggest that, pain, sub mucous fibrosis, palpable neck node, oral site, degree of differentiation and tumor size are the most probable associated factors with extent of nodal involvement. BioMed Central 2020-04-26 /pmc/articles/PMC7183690/ /pubmed/32336269 http://dx.doi.org/10.1186/s12874-020-00985-1 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
Singh, Vishwajeet
Dwivedi, Sada Nand
Deo, S. V. S.
Ordinal logistic regression model describing factors associated with extent of nodal involvement in oral cancer patients and its prospective validation
title Ordinal logistic regression model describing factors associated with extent of nodal involvement in oral cancer patients and its prospective validation
title_full Ordinal logistic regression model describing factors associated with extent of nodal involvement in oral cancer patients and its prospective validation
title_fullStr Ordinal logistic regression model describing factors associated with extent of nodal involvement in oral cancer patients and its prospective validation
title_full_unstemmed Ordinal logistic regression model describing factors associated with extent of nodal involvement in oral cancer patients and its prospective validation
title_short Ordinal logistic regression model describing factors associated with extent of nodal involvement in oral cancer patients and its prospective validation
title_sort ordinal logistic regression model describing factors associated with extent of nodal involvement in oral cancer patients and its prospective validation
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7183690/
https://www.ncbi.nlm.nih.gov/pubmed/32336269
http://dx.doi.org/10.1186/s12874-020-00985-1
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