Lymphocyte density determined by computational pathology validated as a predictor of response to neoadjuvant chemotherapy in breast cancer: secondary analysis of the ARTemis trial
We have previously shown lymphocyte density, measured using computational pathology, is associated with pathological complete response (pCR) in breast cancer. The clinical validity of this finding in independent studies, among patients receiving different chemotherapy, is unknown. The ARTemis trial...
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creator | Ali, H.R. Dariush, A. Thomas, J. Provenzano, E. Dunn, J. Hiller, L. Vallier, A.-L. Abraham, J. Piper, T. Bartlett, J.M.S. Cameron, D.A. Hayward, L. Brenton, J.D. Pharoah, P.D.P. Irwin, M.J. Walton, N.A. Earl, H.M. Caldas, C. |
description | We have previously shown lymphocyte density, measured using computational pathology, is associated with pathological complete response (pCR) in breast cancer. The clinical validity of this finding in independent studies, among patients receiving different chemotherapy, is unknown.
The ARTemis trial randomly assigned 800 women with early stage breast cancer between May 2009 and January 2013 to three cycles of docetaxel, followed by three cycles of fluorouracil, epirubicin and cyclophosphamide once every 21 days with or without four cycles of bevacizumab. The primary endpoint was pCR (absence of invasive cancer in the breast and lymph nodes). We quantified lymphocyte density within haematoxylin and eosin (H&E) whole slide images using our previously described computational pathology approach: for every detected lymphocyte the average distance to the nearest 50 lymphocytes was calculated and the density derived from this statistic. We analyzed both pre-treatment biopsies and post-treatment surgical samples of the tumour bed.
Of the 781 patients originally included in the primary endpoint analysis of the trial, 609 (78%) were included for baseline lymphocyte density analyses and a subset of 383 (49% of 781) for analyses of change in lymphocyte density. The main reason for loss of patients was the availability of digitized whole slide images. Pre-treatment lymphocyte density modelled as a continuous variable was associated with pCR on univariate analysis (odds ratio [OR], 2.92; 95% CI, 1.78–4.85; P |
doi_str_mv | 10.1093/annonc/mdx266 |
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The ARTemis trial randomly assigned 800 women with early stage breast cancer between May 2009 and January 2013 to three cycles of docetaxel, followed by three cycles of fluorouracil, epirubicin and cyclophosphamide once every 21 days with or without four cycles of bevacizumab. The primary endpoint was pCR (absence of invasive cancer in the breast and lymph nodes). We quantified lymphocyte density within haematoxylin and eosin (H&E) whole slide images using our previously described computational pathology approach: for every detected lymphocyte the average distance to the nearest 50 lymphocytes was calculated and the density derived from this statistic. We analyzed both pre-treatment biopsies and post-treatment surgical samples of the tumour bed.
Of the 781 patients originally included in the primary endpoint analysis of the trial, 609 (78%) were included for baseline lymphocyte density analyses and a subset of 383 (49% of 781) for analyses of change in lymphocyte density. The main reason for loss of patients was the availability of digitized whole slide images. Pre-treatment lymphocyte density modelled as a continuous variable was associated with pCR on univariate analysis (odds ratio [OR], 2.92; 95% CI, 1.78–4.85; P < 0.001) and after adjustment for clinical covariates (OR, 2.13; 95% CI, 1.24–3.67; P = 0.006). Increased pre- to post-treatment lymphocyte density showed an independent inverse association with pCR (adjusted OR, 0.1; 95% CI, 0.033–0.31; P < 0.001).
Lymphocyte density in pre-treatment biopsies was validated as an independent predictor of pCR in breast cancer. Computational pathology is emerging as a viable and objective means of identifying predictive biomarkers for cancer patients.
NCT01093235.</description><identifier>ISSN: 0923-7534</identifier><identifier>EISSN: 1569-8041</identifier><identifier>DOI: 10.1093/annonc/mdx266</identifier><identifier>PMID: 28525534</identifier><language>eng</language><publisher>England: Elsevier Ltd</publisher><subject>Antineoplastic Combined Chemotherapy Protocols - therapeutic use ; Bevacizumab - therapeutic use ; breast cancer ; Breast Neoplasms - drug therapy ; Breast Neoplasms - pathology ; Computational Biology ; computational pathology ; Cyclophosphamide - therapeutic use ; Editor's Choice ; Epirubicin - therapeutic use ; Female ; Fluorouracil - therapeutic use ; Humans ; Lymphocyte Count ; Lymphocytes - pathology ; Lymphocytes, Tumor-Infiltrating - pathology ; neoadjuvant chemotherapy ; Neoadjuvant Therapy ; Original ; Polymerase Chain Reaction ; predictive ; Remission Induction ; tumour-infiltrating lymphocytes</subject><ispartof>Annals of oncology, 2017-08, Vol.28 (8), p.1832-1835</ispartof><rights>2017 THE AUTHORS</rights><rights>The Author 2017. Published by Oxford University Press on behalf of the European Society for Medical Oncology.</rights><rights>The Author 2017. Published by Oxford University Press on behalf of the European Society for Medical Oncology. 2017</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c435t-fc09a567b99b1ae66fbd189e5dc8b5dcb445ec4244bf4716ddf17f3345456eb33</citedby><cites>FETCH-LOGICAL-c435t-fc09a567b99b1ae66fbd189e5dc8b5dcb445ec4244bf4716ddf17f3345456eb33</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,314,776,780,881,27901,27902</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/28525534$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Ali, H.R.</creatorcontrib><creatorcontrib>Dariush, A.</creatorcontrib><creatorcontrib>Thomas, J.</creatorcontrib><creatorcontrib>Provenzano, E.</creatorcontrib><creatorcontrib>Dunn, J.</creatorcontrib><creatorcontrib>Hiller, L.</creatorcontrib><creatorcontrib>Vallier, A.-L.</creatorcontrib><creatorcontrib>Abraham, J.</creatorcontrib><creatorcontrib>Piper, T.</creatorcontrib><creatorcontrib>Bartlett, J.M.S.</creatorcontrib><creatorcontrib>Cameron, D.A.</creatorcontrib><creatorcontrib>Hayward, L.</creatorcontrib><creatorcontrib>Brenton, J.D.</creatorcontrib><creatorcontrib>Pharoah, P.D.P.</creatorcontrib><creatorcontrib>Irwin, M.J.</creatorcontrib><creatorcontrib>Walton, N.A.</creatorcontrib><creatorcontrib>Earl, H.M.</creatorcontrib><creatorcontrib>Caldas, C.</creatorcontrib><title>Lymphocyte density determined by computational pathology validated as a predictor of response to neoadjuvant chemotherapy in breast cancer: secondary analysis of the ARTemis trial</title><title>Annals of oncology</title><addtitle>Ann Oncol</addtitle><description>We have previously shown lymphocyte density, measured using computational pathology, is associated with pathological complete response (pCR) in breast cancer. The clinical validity of this finding in independent studies, among patients receiving different chemotherapy, is unknown.
The ARTemis trial randomly assigned 800 women with early stage breast cancer between May 2009 and January 2013 to three cycles of docetaxel, followed by three cycles of fluorouracil, epirubicin and cyclophosphamide once every 21 days with or without four cycles of bevacizumab. The primary endpoint was pCR (absence of invasive cancer in the breast and lymph nodes). We quantified lymphocyte density within haematoxylin and eosin (H&E) whole slide images using our previously described computational pathology approach: for every detected lymphocyte the average distance to the nearest 50 lymphocytes was calculated and the density derived from this statistic. We analyzed both pre-treatment biopsies and post-treatment surgical samples of the tumour bed.
Of the 781 patients originally included in the primary endpoint analysis of the trial, 609 (78%) were included for baseline lymphocyte density analyses and a subset of 383 (49% of 781) for analyses of change in lymphocyte density. The main reason for loss of patients was the availability of digitized whole slide images. Pre-treatment lymphocyte density modelled as a continuous variable was associated with pCR on univariate analysis (odds ratio [OR], 2.92; 95% CI, 1.78–4.85; P < 0.001) and after adjustment for clinical covariates (OR, 2.13; 95% CI, 1.24–3.67; P = 0.006). Increased pre- to post-treatment lymphocyte density showed an independent inverse association with pCR (adjusted OR, 0.1; 95% CI, 0.033–0.31; P < 0.001).
Lymphocyte density in pre-treatment biopsies was validated as an independent predictor of pCR in breast cancer. Computational pathology is emerging as a viable and objective means of identifying predictive biomarkers for cancer patients.
NCT01093235.</description><subject>Antineoplastic Combined Chemotherapy Protocols - therapeutic use</subject><subject>Bevacizumab - therapeutic use</subject><subject>breast cancer</subject><subject>Breast Neoplasms - drug therapy</subject><subject>Breast Neoplasms - pathology</subject><subject>Computational Biology</subject><subject>computational pathology</subject><subject>Cyclophosphamide - therapeutic use</subject><subject>Editor's Choice</subject><subject>Epirubicin - therapeutic use</subject><subject>Female</subject><subject>Fluorouracil - therapeutic use</subject><subject>Humans</subject><subject>Lymphocyte Count</subject><subject>Lymphocytes - pathology</subject><subject>Lymphocytes, Tumor-Infiltrating - pathology</subject><subject>neoadjuvant chemotherapy</subject><subject>Neoadjuvant Therapy</subject><subject>Original</subject><subject>Polymerase Chain Reaction</subject><subject>predictive</subject><subject>Remission Induction</subject><subject>tumour-infiltrating lymphocytes</subject><issn>0923-7534</issn><issn>1569-8041</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp1kcuKFTEQhoMoznF06VbyAu0k3UlfXAjD4A0OCDKuQyWpns7QnTRJzsF-Ll_QDK2DLtykSOWrvyr1E_Kas7ecDc0VeB-8uVrsj7ptn5ADl-1Q9Uzwp-TAhrqpOtmIC_IipXvGWDvUw3NyUfeyliV_ID-P27JOwWwZqUWfXN5KzBgX59FSvVETlvWUIbvgYaYr5CnM4W6jZ5idhVwgSBToGtE6k0OkYaQR0xp8QpoD9RjA3p_O4DM1Ey4hTxhh3ajzVEeEVNLgDcZ3NKEJ3kLcKJReW3LpQazw9PrbLS7lmqOD-SV5NsKc8NXveEm-f_xwe_O5On799OXm-lgZ0chcjYYNINtOD4PmgG07asv7AaU1vS6HFkKiEbUQehQdb60deTc2jZBCtqib5pK833XXk17QGvQ5wqzW6JYyowrg1L8v3k3qLpyV7BvBOCsC1S5gYkgp4vhYy5l6cE_t7qndvcK_-bvhI_3HrgJ0O4Dl22eHUSXjsCzPuogmKxvcf6R_Af7Gs_8</recordid><startdate>20170801</startdate><enddate>20170801</enddate><creator>Ali, H.R.</creator><creator>Dariush, A.</creator><creator>Thomas, J.</creator><creator>Provenzano, E.</creator><creator>Dunn, J.</creator><creator>Hiller, L.</creator><creator>Vallier, A.-L.</creator><creator>Abraham, J.</creator><creator>Piper, T.</creator><creator>Bartlett, J.M.S.</creator><creator>Cameron, D.A.</creator><creator>Hayward, L.</creator><creator>Brenton, J.D.</creator><creator>Pharoah, P.D.P.</creator><creator>Irwin, M.J.</creator><creator>Walton, N.A.</creator><creator>Earl, H.M.</creator><creator>Caldas, C.</creator><general>Elsevier Ltd</general><general>Oxford University Press</general><scope>6I.</scope><scope>AAFTH</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>5PM</scope></search><sort><creationdate>20170801</creationdate><title>Lymphocyte density determined by computational pathology validated as a predictor of response to neoadjuvant chemotherapy in breast cancer: secondary analysis of the ARTemis trial</title><author>Ali, H.R. ; Dariush, A. ; Thomas, J. ; Provenzano, E. ; Dunn, J. ; Hiller, L. ; Vallier, A.-L. ; Abraham, J. ; Piper, T. ; Bartlett, J.M.S. ; Cameron, D.A. ; Hayward, L. ; Brenton, J.D. ; Pharoah, P.D.P. ; Irwin, M.J. ; Walton, N.A. ; Earl, H.M. ; Caldas, C.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c435t-fc09a567b99b1ae66fbd189e5dc8b5dcb445ec4244bf4716ddf17f3345456eb33</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Antineoplastic Combined Chemotherapy Protocols - therapeutic use</topic><topic>Bevacizumab - therapeutic use</topic><topic>breast cancer</topic><topic>Breast Neoplasms - drug therapy</topic><topic>Breast Neoplasms - pathology</topic><topic>Computational Biology</topic><topic>computational pathology</topic><topic>Cyclophosphamide - therapeutic use</topic><topic>Editor's Choice</topic><topic>Epirubicin - therapeutic use</topic><topic>Female</topic><topic>Fluorouracil - therapeutic use</topic><topic>Humans</topic><topic>Lymphocyte Count</topic><topic>Lymphocytes - pathology</topic><topic>Lymphocytes, Tumor-Infiltrating - pathology</topic><topic>neoadjuvant chemotherapy</topic><topic>Neoadjuvant Therapy</topic><topic>Original</topic><topic>Polymerase Chain Reaction</topic><topic>predictive</topic><topic>Remission Induction</topic><topic>tumour-infiltrating lymphocytes</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ali, H.R.</creatorcontrib><creatorcontrib>Dariush, A.</creatorcontrib><creatorcontrib>Thomas, J.</creatorcontrib><creatorcontrib>Provenzano, E.</creatorcontrib><creatorcontrib>Dunn, J.</creatorcontrib><creatorcontrib>Hiller, L.</creatorcontrib><creatorcontrib>Vallier, A.-L.</creatorcontrib><creatorcontrib>Abraham, J.</creatorcontrib><creatorcontrib>Piper, T.</creatorcontrib><creatorcontrib>Bartlett, J.M.S.</creatorcontrib><creatorcontrib>Cameron, D.A.</creatorcontrib><creatorcontrib>Hayward, L.</creatorcontrib><creatorcontrib>Brenton, J.D.</creatorcontrib><creatorcontrib>Pharoah, P.D.P.</creatorcontrib><creatorcontrib>Irwin, M.J.</creatorcontrib><creatorcontrib>Walton, N.A.</creatorcontrib><creatorcontrib>Earl, H.M.</creatorcontrib><creatorcontrib>Caldas, C.</creatorcontrib><collection>ScienceDirect Open Access Titles</collection><collection>Elsevier:ScienceDirect:Open Access</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Annals of oncology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ali, H.R.</au><au>Dariush, A.</au><au>Thomas, J.</au><au>Provenzano, E.</au><au>Dunn, J.</au><au>Hiller, L.</au><au>Vallier, A.-L.</au><au>Abraham, J.</au><au>Piper, T.</au><au>Bartlett, J.M.S.</au><au>Cameron, D.A.</au><au>Hayward, L.</au><au>Brenton, J.D.</au><au>Pharoah, P.D.P.</au><au>Irwin, M.J.</au><au>Walton, N.A.</au><au>Earl, H.M.</au><au>Caldas, C.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Lymphocyte density determined by computational pathology validated as a predictor of response to neoadjuvant chemotherapy in breast cancer: secondary analysis of the ARTemis trial</atitle><jtitle>Annals of oncology</jtitle><addtitle>Ann Oncol</addtitle><date>2017-08-01</date><risdate>2017</risdate><volume>28</volume><issue>8</issue><spage>1832</spage><epage>1835</epage><pages>1832-1835</pages><issn>0923-7534</issn><eissn>1569-8041</eissn><abstract>We have previously shown lymphocyte density, measured using computational pathology, is associated with pathological complete response (pCR) in breast cancer. The clinical validity of this finding in independent studies, among patients receiving different chemotherapy, is unknown.
The ARTemis trial randomly assigned 800 women with early stage breast cancer between May 2009 and January 2013 to three cycles of docetaxel, followed by three cycles of fluorouracil, epirubicin and cyclophosphamide once every 21 days with or without four cycles of bevacizumab. The primary endpoint was pCR (absence of invasive cancer in the breast and lymph nodes). We quantified lymphocyte density within haematoxylin and eosin (H&E) whole slide images using our previously described computational pathology approach: for every detected lymphocyte the average distance to the nearest 50 lymphocytes was calculated and the density derived from this statistic. We analyzed both pre-treatment biopsies and post-treatment surgical samples of the tumour bed.
Of the 781 patients originally included in the primary endpoint analysis of the trial, 609 (78%) were included for baseline lymphocyte density analyses and a subset of 383 (49% of 781) for analyses of change in lymphocyte density. The main reason for loss of patients was the availability of digitized whole slide images. Pre-treatment lymphocyte density modelled as a continuous variable was associated with pCR on univariate analysis (odds ratio [OR], 2.92; 95% CI, 1.78–4.85; P < 0.001) and after adjustment for clinical covariates (OR, 2.13; 95% CI, 1.24–3.67; P = 0.006). Increased pre- to post-treatment lymphocyte density showed an independent inverse association with pCR (adjusted OR, 0.1; 95% CI, 0.033–0.31; P < 0.001).
Lymphocyte density in pre-treatment biopsies was validated as an independent predictor of pCR in breast cancer. Computational pathology is emerging as a viable and objective means of identifying predictive biomarkers for cancer patients.
NCT01093235.</abstract><cop>England</cop><pub>Elsevier Ltd</pub><pmid>28525534</pmid><doi>10.1093/annonc/mdx266</doi><tpages>4</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Antineoplastic Combined Chemotherapy Protocols - therapeutic use Bevacizumab - therapeutic use breast cancer Breast Neoplasms - drug therapy Breast Neoplasms - pathology Computational Biology computational pathology Cyclophosphamide - therapeutic use Editor's Choice Epirubicin - therapeutic use Female Fluorouracil - therapeutic use Humans Lymphocyte Count Lymphocytes - pathology Lymphocytes, Tumor-Infiltrating - pathology neoadjuvant chemotherapy Neoadjuvant Therapy Original Polymerase Chain Reaction predictive Remission Induction tumour-infiltrating lymphocytes |
title | Lymphocyte density determined by computational pathology validated as a predictor of response to neoadjuvant chemotherapy in breast cancer: secondary analysis of the ARTemis trial |
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