Cargando…

A multi‐institutional prediction model to estimate the risk of recurrence and mortality after mastectomy for T1‐2N1 breast cancer

BACKGROUND: Post‐mastectomy radiation therapy (PMRT) in women with pathologic stage T1‐2N1M0 breast cancer is controversial. METHODS: Data from five North American institutions including women undergoing mastectomy without neoadjuvant therapy with pT1‐2N1M0 breast cancer treated from 2006 to 2015 we...

Descripción completa

Detalles Bibliográficos
Autores principales: Sittenfeld, Sarah M. C., Zabor, Emily C., Hamilton, Sarah N., Kuerer, Henry M., El‐Tamer, Mahmoud, Naoum, George E., Truong, Pauline T., Nichol, Alan, Smith, Benjamin D., Woodward, Wendy A., Moo, Tracy‐Ann, Powell, Simon N., Shah, Chirag S., Taghian, Alphonse G., Abu‐Gheida, Ibrahim, Tendulkar, Rahul D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9539507/
https://www.ncbi.nlm.nih.gov/pubmed/35713598
http://dx.doi.org/10.1002/cncr.34352
_version_ 1784803503362801664
author Sittenfeld, Sarah M. C.
Zabor, Emily C.
Hamilton, Sarah N.
Kuerer, Henry M.
El‐Tamer, Mahmoud
Naoum, George E.
Truong, Pauline T.
Nichol, Alan
Smith, Benjamin D.
Woodward, Wendy A.
Moo, Tracy‐Ann
Powell, Simon N.
Shah, Chirag S.
Taghian, Alphonse G.
Abu‐Gheida, Ibrahim
Tendulkar, Rahul D.
author_facet Sittenfeld, Sarah M. C.
Zabor, Emily C.
Hamilton, Sarah N.
Kuerer, Henry M.
El‐Tamer, Mahmoud
Naoum, George E.
Truong, Pauline T.
Nichol, Alan
Smith, Benjamin D.
Woodward, Wendy A.
Moo, Tracy‐Ann
Powell, Simon N.
Shah, Chirag S.
Taghian, Alphonse G.
Abu‐Gheida, Ibrahim
Tendulkar, Rahul D.
author_sort Sittenfeld, Sarah M. C.
collection PubMed
description BACKGROUND: Post‐mastectomy radiation therapy (PMRT) in women with pathologic stage T1‐2N1M0 breast cancer is controversial. METHODS: Data from five North American institutions including women undergoing mastectomy without neoadjuvant therapy with pT1‐2N1M0 breast cancer treated from 2006 to 2015 were pooled for analysis. Competing‐risks regression was performed to identify factors associated with locoregional recurrence (LRR), distant metastasis (DM), overall recurrence (OR), and breast cancer mortality (BCM). RESULTS: A total of 3532 patients were included for analysis with a median follow‐up time among survivors of 6.8 years (interquartile range [IQR], 4.5–9.5 years). The 2154 (61%) patients who received PMRT had significantly more adverse risk factors than those patients not receiving PMRT: younger age, larger tumors, more positive lymph nodes, lymphovascular invasion, extracapsular extension, and positive margins (p < .05 for all). On competing risk regression analysis, receipt of PMRT was significantly associated with a decreased risk of LRR (hazard ratio [HR], 0.21; 95% confidence interval [CI], 0.14–0.31; p < .001) and OR (HR, 0.76; 95% CI, 0.62–0.94; p = .011). Model performance metrics for each end point showed good discrimination and calibration. An online prediction model to estimate predicted risks for each outcome based on individual patient and tumor characteristics was created from the model. CONCLUSIONS: In a large multi‐institutional cohort of patients, PMRT for T1‐2N1 breast cancer was associated with a significant reduction in locoregional and overall recurrence after accounting for known prognostic factors. An online calculator was developed to aid in personalized decision‐making regarding PMRT in this population.
format Online
Article
Text
id pubmed-9539507
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher John Wiley and Sons Inc.
record_format MEDLINE/PubMed
spelling pubmed-95395072022-10-14 A multi‐institutional prediction model to estimate the risk of recurrence and mortality after mastectomy for T1‐2N1 breast cancer Sittenfeld, Sarah M. C. Zabor, Emily C. Hamilton, Sarah N. Kuerer, Henry M. El‐Tamer, Mahmoud Naoum, George E. Truong, Pauline T. Nichol, Alan Smith, Benjamin D. Woodward, Wendy A. Moo, Tracy‐Ann Powell, Simon N. Shah, Chirag S. Taghian, Alphonse G. Abu‐Gheida, Ibrahim Tendulkar, Rahul D. Cancer Original Articles BACKGROUND: Post‐mastectomy radiation therapy (PMRT) in women with pathologic stage T1‐2N1M0 breast cancer is controversial. METHODS: Data from five North American institutions including women undergoing mastectomy without neoadjuvant therapy with pT1‐2N1M0 breast cancer treated from 2006 to 2015 were pooled for analysis. Competing‐risks regression was performed to identify factors associated with locoregional recurrence (LRR), distant metastasis (DM), overall recurrence (OR), and breast cancer mortality (BCM). RESULTS: A total of 3532 patients were included for analysis with a median follow‐up time among survivors of 6.8 years (interquartile range [IQR], 4.5–9.5 years). The 2154 (61%) patients who received PMRT had significantly more adverse risk factors than those patients not receiving PMRT: younger age, larger tumors, more positive lymph nodes, lymphovascular invasion, extracapsular extension, and positive margins (p < .05 for all). On competing risk regression analysis, receipt of PMRT was significantly associated with a decreased risk of LRR (hazard ratio [HR], 0.21; 95% confidence interval [CI], 0.14–0.31; p < .001) and OR (HR, 0.76; 95% CI, 0.62–0.94; p = .011). Model performance metrics for each end point showed good discrimination and calibration. An online prediction model to estimate predicted risks for each outcome based on individual patient and tumor characteristics was created from the model. CONCLUSIONS: In a large multi‐institutional cohort of patients, PMRT for T1‐2N1 breast cancer was associated with a significant reduction in locoregional and overall recurrence after accounting for known prognostic factors. An online calculator was developed to aid in personalized decision‐making regarding PMRT in this population. John Wiley and Sons Inc. 2022-06-17 2022-08-15 /pmc/articles/PMC9539507/ /pubmed/35713598 http://dx.doi.org/10.1002/cncr.34352 Text en © 2022 The Authors. Cancer published by Wiley Periodicals LLC on behalf of American Cancer Society. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
spellingShingle Original Articles
Sittenfeld, Sarah M. C.
Zabor, Emily C.
Hamilton, Sarah N.
Kuerer, Henry M.
El‐Tamer, Mahmoud
Naoum, George E.
Truong, Pauline T.
Nichol, Alan
Smith, Benjamin D.
Woodward, Wendy A.
Moo, Tracy‐Ann
Powell, Simon N.
Shah, Chirag S.
Taghian, Alphonse G.
Abu‐Gheida, Ibrahim
Tendulkar, Rahul D.
A multi‐institutional prediction model to estimate the risk of recurrence and mortality after mastectomy for T1‐2N1 breast cancer
title A multi‐institutional prediction model to estimate the risk of recurrence and mortality after mastectomy for T1‐2N1 breast cancer
title_full A multi‐institutional prediction model to estimate the risk of recurrence and mortality after mastectomy for T1‐2N1 breast cancer
title_fullStr A multi‐institutional prediction model to estimate the risk of recurrence and mortality after mastectomy for T1‐2N1 breast cancer
title_full_unstemmed A multi‐institutional prediction model to estimate the risk of recurrence and mortality after mastectomy for T1‐2N1 breast cancer
title_short A multi‐institutional prediction model to estimate the risk of recurrence and mortality after mastectomy for T1‐2N1 breast cancer
title_sort multi‐institutional prediction model to estimate the risk of recurrence and mortality after mastectomy for t1‐2n1 breast cancer
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9539507/
https://www.ncbi.nlm.nih.gov/pubmed/35713598
http://dx.doi.org/10.1002/cncr.34352
work_keys_str_mv AT sittenfeldsarahmc amultiinstitutionalpredictionmodeltoestimatetheriskofrecurrenceandmortalityaftermastectomyfort12n1breastcancer
AT zaboremilyc amultiinstitutionalpredictionmodeltoestimatetheriskofrecurrenceandmortalityaftermastectomyfort12n1breastcancer
AT hamiltonsarahn amultiinstitutionalpredictionmodeltoestimatetheriskofrecurrenceandmortalityaftermastectomyfort12n1breastcancer
AT kuererhenrym amultiinstitutionalpredictionmodeltoestimatetheriskofrecurrenceandmortalityaftermastectomyfort12n1breastcancer
AT eltamermahmoud amultiinstitutionalpredictionmodeltoestimatetheriskofrecurrenceandmortalityaftermastectomyfort12n1breastcancer
AT naoumgeorgee amultiinstitutionalpredictionmodeltoestimatetheriskofrecurrenceandmortalityaftermastectomyfort12n1breastcancer
AT truongpaulinet amultiinstitutionalpredictionmodeltoestimatetheriskofrecurrenceandmortalityaftermastectomyfort12n1breastcancer
AT nicholalan amultiinstitutionalpredictionmodeltoestimatetheriskofrecurrenceandmortalityaftermastectomyfort12n1breastcancer
AT smithbenjamind amultiinstitutionalpredictionmodeltoestimatetheriskofrecurrenceandmortalityaftermastectomyfort12n1breastcancer
AT woodwardwendya amultiinstitutionalpredictionmodeltoestimatetheriskofrecurrenceandmortalityaftermastectomyfort12n1breastcancer
AT mootracyann amultiinstitutionalpredictionmodeltoestimatetheriskofrecurrenceandmortalityaftermastectomyfort12n1breastcancer
AT powellsimonn amultiinstitutionalpredictionmodeltoestimatetheriskofrecurrenceandmortalityaftermastectomyfort12n1breastcancer
AT shahchirags amultiinstitutionalpredictionmodeltoestimatetheriskofrecurrenceandmortalityaftermastectomyfort12n1breastcancer
AT taghianalphonseg amultiinstitutionalpredictionmodeltoestimatetheriskofrecurrenceandmortalityaftermastectomyfort12n1breastcancer
AT abugheidaibrahim amultiinstitutionalpredictionmodeltoestimatetheriskofrecurrenceandmortalityaftermastectomyfort12n1breastcancer
AT tendulkarrahuld amultiinstitutionalpredictionmodeltoestimatetheriskofrecurrenceandmortalityaftermastectomyfort12n1breastcancer
AT sittenfeldsarahmc multiinstitutionalpredictionmodeltoestimatetheriskofrecurrenceandmortalityaftermastectomyfort12n1breastcancer
AT zaboremilyc multiinstitutionalpredictionmodeltoestimatetheriskofrecurrenceandmortalityaftermastectomyfort12n1breastcancer
AT hamiltonsarahn multiinstitutionalpredictionmodeltoestimatetheriskofrecurrenceandmortalityaftermastectomyfort12n1breastcancer
AT kuererhenrym multiinstitutionalpredictionmodeltoestimatetheriskofrecurrenceandmortalityaftermastectomyfort12n1breastcancer
AT eltamermahmoud multiinstitutionalpredictionmodeltoestimatetheriskofrecurrenceandmortalityaftermastectomyfort12n1breastcancer
AT naoumgeorgee multiinstitutionalpredictionmodeltoestimatetheriskofrecurrenceandmortalityaftermastectomyfort12n1breastcancer
AT truongpaulinet multiinstitutionalpredictionmodeltoestimatetheriskofrecurrenceandmortalityaftermastectomyfort12n1breastcancer
AT nicholalan multiinstitutionalpredictionmodeltoestimatetheriskofrecurrenceandmortalityaftermastectomyfort12n1breastcancer
AT smithbenjamind multiinstitutionalpredictionmodeltoestimatetheriskofrecurrenceandmortalityaftermastectomyfort12n1breastcancer
AT woodwardwendya multiinstitutionalpredictionmodeltoestimatetheriskofrecurrenceandmortalityaftermastectomyfort12n1breastcancer
AT mootracyann multiinstitutionalpredictionmodeltoestimatetheriskofrecurrenceandmortalityaftermastectomyfort12n1breastcancer
AT powellsimonn multiinstitutionalpredictionmodeltoestimatetheriskofrecurrenceandmortalityaftermastectomyfort12n1breastcancer
AT shahchirags multiinstitutionalpredictionmodeltoestimatetheriskofrecurrenceandmortalityaftermastectomyfort12n1breastcancer
AT taghianalphonseg multiinstitutionalpredictionmodeltoestimatetheriskofrecurrenceandmortalityaftermastectomyfort12n1breastcancer
AT abugheidaibrahim multiinstitutionalpredictionmodeltoestimatetheriskofrecurrenceandmortalityaftermastectomyfort12n1breastcancer
AT tendulkarrahuld multiinstitutionalpredictionmodeltoestimatetheriskofrecurrenceandmortalityaftermastectomyfort12n1breastcancer