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Pre-Treatment Tumor Growth Rate Predicts Clinical Outcomes of Patients With Advanced Non-Small Cell Lung Cancer Undergoing Anti-PD-1/PD-L1 Therapy
Tumor growth rate (TGR; percent size change per month [%/m]) is postulated as an early radio-graphic predictor of response to anti-cancer treatment to overcome limitations of RECIST. We aimed to evaluate the predictive value of pre-treatment TGR (TGR ) for outcomes of advanced non-small cell lung ca...
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Published in: | Frontiers in oncology 2021-01, Vol.10, p.621329-621329 |
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creator | He, Li-Na Zhang, Xuanye Li, Haifeng Chen, Tao Chen, Chen Zhou, Yixin Lin, Zuan Du, Wei Fang, Wenfeng Yang, Yunpeng Huang, Yan Zhao, Hongyun Hong, Shaodong Zhang, Li |
description | Tumor growth rate (TGR; percent size change per month [%/m]) is postulated as an early radio-graphic predictor of response to anti-cancer treatment to overcome limitations of RECIST. We aimed to evaluate the predictive value of pre-treatment TGR (TGR
) for outcomes of advanced non-small cell lung cancer (aNSCLC) patients treated with anti-PD-1/PD-L1 monotherapy. We retrospectively screened all aNSCLC patients who received PD-1 axis inhibitors in Sun Yat-Sen University Cancer Center between August 2016 and June 2018. TGR
was calculated as the percentage change in tumor size per month (%/m) derived from two computed tomography (CT) scans during a "wash-out" period before the initiation of PD-1 axis inhibition. Final follow-up date was August 28, 2019. The X-tile program was used to identify the cut-off value of TGR
based on maximum progression-free survival (PFS) stratification. Patients were divided into two groups per the selected TGR
cut-off. The primary outcome was the difference of PFS between the two groups. The Kaplan-Meier methods and Cox regression models were performed for survival analysis. A total of 80 eligible patients were included (54 [67.5%] male; median [range] age, 55 [30-74] years). Median (range) TGR
was 21.1 (-33.7-246.0)%/m. The optimal cut-off value of TGR
was 25.3%/m. Patients with high TGR
had shorter median PFS (1.8 months; 95% CI, 1.6 - 2.1 months) than those with low TGR
(2.7 months; 95% CI, 0.5 - 4.9 months) (
= 0.005). Multivariate Cox regression analysis revealed that higher TGR
independently predicted inferior PFS (hazard ratio [HR] 1.97; 95% CI, 1.08-3.60;
= 0.026). Higher TGR
was also significantly associated with less durable clinical benefit rate (34.8% vs. 8.8%,
= 0.007). High pre-treatment TGR was a reliable predictor of inferior PFS and clinical benefit in aNSCLC patients undergoing anti-PD-1/PD-L1 monotherapy. The findings highlight the role of TGR
as an early biomarker to predict benefit from immunotherapy and could allow tailoring patient's follow-up. |
doi_str_mv | 10.3389/fonc.2020.621329 |
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) for outcomes of advanced non-small cell lung cancer (aNSCLC) patients treated with anti-PD-1/PD-L1 monotherapy. We retrospectively screened all aNSCLC patients who received PD-1 axis inhibitors in Sun Yat-Sen University Cancer Center between August 2016 and June 2018. TGR
was calculated as the percentage change in tumor size per month (%/m) derived from two computed tomography (CT) scans during a "wash-out" period before the initiation of PD-1 axis inhibition. Final follow-up date was August 28, 2019. The X-tile program was used to identify the cut-off value of TGR
based on maximum progression-free survival (PFS) stratification. Patients were divided into two groups per the selected TGR
cut-off. The primary outcome was the difference of PFS between the two groups. The Kaplan-Meier methods and Cox regression models were performed for survival analysis. A total of 80 eligible patients were included (54 [67.5%] male; median [range] age, 55 [30-74] years). Median (range) TGR
was 21.1 (-33.7-246.0)%/m. The optimal cut-off value of TGR
was 25.3%/m. Patients with high TGR
had shorter median PFS (1.8 months; 95% CI, 1.6 - 2.1 months) than those with low TGR
(2.7 months; 95% CI, 0.5 - 4.9 months) (
= 0.005). Multivariate Cox regression analysis revealed that higher TGR
independently predicted inferior PFS (hazard ratio [HR] 1.97; 95% CI, 1.08-3.60;
= 0.026). Higher TGR
was also significantly associated with less durable clinical benefit rate (34.8% vs. 8.8%,
= 0.007). High pre-treatment TGR was a reliable predictor of inferior PFS and clinical benefit in aNSCLC patients undergoing anti-PD-1/PD-L1 monotherapy. The findings highlight the role of TGR
as an early biomarker to predict benefit from immunotherapy and could allow tailoring patient's follow-up.</description><identifier>ISSN: 2234-943X</identifier><identifier>EISSN: 2234-943X</identifier><identifier>DOI: 10.3389/fonc.2020.621329</identifier><identifier>PMID: 33552993</identifier><language>eng</language><publisher>Switzerland: Frontiers Media S.A</publisher><subject>anti-PD-1/PD-L1 therapy ; immunotherapy ; non-small cell lung cancer ; NSCLC ; Oncology ; progression-free survival ; tumor growth rate</subject><ispartof>Frontiers in oncology, 2021-01, Vol.10, p.621329-621329</ispartof><rights>Copyright © 2021 He, Zhang, Li, Chen, Chen, Zhou, Lin, Du, Fang, Yang, Huang, Zhao, Hong and Zhang.</rights><rights>Copyright © 2021 He, Zhang, Li, Chen, Chen, Zhou, Lin, Du, Fang, Yang, Huang, Zhao, Hong and Zhang 2021 He, Zhang, Li, Chen, Chen, Zhou, Lin, Du, Fang, Yang, Huang, Zhao, Hong and Zhang</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c462t-7d553a531ad3dd42e835e131d8598779efcadfaecb199f134b27c9034f0a922e3</citedby><cites>FETCH-LOGICAL-c462t-7d553a531ad3dd42e835e131d8598779efcadfaecb199f134b27c9034f0a922e3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7863973/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7863973/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,27924,27925,53791,53793</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/33552993$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>He, Li-Na</creatorcontrib><creatorcontrib>Zhang, Xuanye</creatorcontrib><creatorcontrib>Li, Haifeng</creatorcontrib><creatorcontrib>Chen, Tao</creatorcontrib><creatorcontrib>Chen, Chen</creatorcontrib><creatorcontrib>Zhou, Yixin</creatorcontrib><creatorcontrib>Lin, Zuan</creatorcontrib><creatorcontrib>Du, Wei</creatorcontrib><creatorcontrib>Fang, Wenfeng</creatorcontrib><creatorcontrib>Yang, Yunpeng</creatorcontrib><creatorcontrib>Huang, Yan</creatorcontrib><creatorcontrib>Zhao, Hongyun</creatorcontrib><creatorcontrib>Hong, Shaodong</creatorcontrib><creatorcontrib>Zhang, Li</creatorcontrib><title>Pre-Treatment Tumor Growth Rate Predicts Clinical Outcomes of Patients With Advanced Non-Small Cell Lung Cancer Undergoing Anti-PD-1/PD-L1 Therapy</title><title>Frontiers in oncology</title><addtitle>Front Oncol</addtitle><description>Tumor growth rate (TGR; percent size change per month [%/m]) is postulated as an early radio-graphic predictor of response to anti-cancer treatment to overcome limitations of RECIST. We aimed to evaluate the predictive value of pre-treatment TGR (TGR
) for outcomes of advanced non-small cell lung cancer (aNSCLC) patients treated with anti-PD-1/PD-L1 monotherapy. We retrospectively screened all aNSCLC patients who received PD-1 axis inhibitors in Sun Yat-Sen University Cancer Center between August 2016 and June 2018. TGR
was calculated as the percentage change in tumor size per month (%/m) derived from two computed tomography (CT) scans during a "wash-out" period before the initiation of PD-1 axis inhibition. Final follow-up date was August 28, 2019. The X-tile program was used to identify the cut-off value of TGR
based on maximum progression-free survival (PFS) stratification. Patients were divided into two groups per the selected TGR
cut-off. The primary outcome was the difference of PFS between the two groups. The Kaplan-Meier methods and Cox regression models were performed for survival analysis. A total of 80 eligible patients were included (54 [67.5%] male; median [range] age, 55 [30-74] years). Median (range) TGR
was 21.1 (-33.7-246.0)%/m. The optimal cut-off value of TGR
was 25.3%/m. Patients with high TGR
had shorter median PFS (1.8 months; 95% CI, 1.6 - 2.1 months) than those with low TGR
(2.7 months; 95% CI, 0.5 - 4.9 months) (
= 0.005). Multivariate Cox regression analysis revealed that higher TGR
independently predicted inferior PFS (hazard ratio [HR] 1.97; 95% CI, 1.08-3.60;
= 0.026). Higher TGR
was also significantly associated with less durable clinical benefit rate (34.8% vs. 8.8%,
= 0.007). High pre-treatment TGR was a reliable predictor of inferior PFS and clinical benefit in aNSCLC patients undergoing anti-PD-1/PD-L1 monotherapy. The findings highlight the role of TGR
as an early biomarker to predict benefit from immunotherapy and could allow tailoring patient's follow-up.</description><subject>anti-PD-1/PD-L1 therapy</subject><subject>immunotherapy</subject><subject>non-small cell lung cancer</subject><subject>NSCLC</subject><subject>Oncology</subject><subject>progression-free survival</subject><subject>tumor growth rate</subject><issn>2234-943X</issn><issn>2234-943X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>DOA</sourceid><recordid>eNpVksFuEzEQhlcIRKvSOyfkI5dNbY-dXV-QogClUkQjSAU3y7G9iatdO9jeor4GT4yXlKr1YTyamf-zNfqr6i3BM4BWXHTB6xnFFM_mlAAVL6pTSoHVgsHPl0_yk-o8pVtczpxjguF1dQLAORUCTqs_62jrTbQqD9ZntBmHENFlDL_zHn1T2aLSN07nhJa9806rHl2PWYfBJhQ6tFbZFV1CP1wRLMyd8toa9DX4-vug-h4tbQmr0e_QcmpFdOONjbvgSmXhs6vXH2tyUcKKoM3eRnW4f1O96lSf7PnDfVbdfP60WX6pV9eXV8vFqtZsTnPdGM5BcSDKgDGM2ha4JUBMy0XbNMJ2WplOWb0lQnQE2JY2WmBgHVaCUgtn1dWRa4K6lYfoBhXvZVBO_iuEuJMqZqd7KwE3hG8F11RTpikIq0ABJ1R0mhkDhfXhyDqM28EaXXYSVf8M-rzj3V7uwp1s2jmIZgK8fwDE8Gu0KcvBJV2Wp7wNY5KUtQ2jDWNtGcXHUR1DStF2j88QLCdnyMkZcnKGPDqjSN49_d6j4L8P4C_5obWo</recordid><startdate>20210119</startdate><enddate>20210119</enddate><creator>He, Li-Na</creator><creator>Zhang, Xuanye</creator><creator>Li, Haifeng</creator><creator>Chen, Tao</creator><creator>Chen, Chen</creator><creator>Zhou, Yixin</creator><creator>Lin, Zuan</creator><creator>Du, Wei</creator><creator>Fang, Wenfeng</creator><creator>Yang, Yunpeng</creator><creator>Huang, Yan</creator><creator>Zhao, Hongyun</creator><creator>Hong, Shaodong</creator><creator>Zhang, Li</creator><general>Frontiers Media S.A</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope></search><sort><creationdate>20210119</creationdate><title>Pre-Treatment Tumor Growth Rate Predicts Clinical Outcomes of Patients With Advanced Non-Small Cell Lung Cancer Undergoing Anti-PD-1/PD-L1 Therapy</title><author>He, Li-Na ; Zhang, Xuanye ; Li, Haifeng ; Chen, Tao ; Chen, Chen ; Zhou, Yixin ; Lin, Zuan ; Du, Wei ; Fang, Wenfeng ; Yang, Yunpeng ; Huang, Yan ; Zhao, Hongyun ; Hong, Shaodong ; Zhang, Li</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c462t-7d553a531ad3dd42e835e131d8598779efcadfaecb199f134b27c9034f0a922e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>anti-PD-1/PD-L1 therapy</topic><topic>immunotherapy</topic><topic>non-small cell lung cancer</topic><topic>NSCLC</topic><topic>Oncology</topic><topic>progression-free survival</topic><topic>tumor growth rate</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>He, Li-Na</creatorcontrib><creatorcontrib>Zhang, Xuanye</creatorcontrib><creatorcontrib>Li, Haifeng</creatorcontrib><creatorcontrib>Chen, Tao</creatorcontrib><creatorcontrib>Chen, Chen</creatorcontrib><creatorcontrib>Zhou, Yixin</creatorcontrib><creatorcontrib>Lin, Zuan</creatorcontrib><creatorcontrib>Du, Wei</creatorcontrib><creatorcontrib>Fang, Wenfeng</creatorcontrib><creatorcontrib>Yang, Yunpeng</creatorcontrib><creatorcontrib>Huang, Yan</creatorcontrib><creatorcontrib>Zhao, Hongyun</creatorcontrib><creatorcontrib>Hong, Shaodong</creatorcontrib><creatorcontrib>Zhang, Li</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>Directory of Open Access Journals</collection><jtitle>Frontiers in oncology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>He, Li-Na</au><au>Zhang, Xuanye</au><au>Li, Haifeng</au><au>Chen, Tao</au><au>Chen, Chen</au><au>Zhou, Yixin</au><au>Lin, Zuan</au><au>Du, Wei</au><au>Fang, Wenfeng</au><au>Yang, Yunpeng</au><au>Huang, Yan</au><au>Zhao, Hongyun</au><au>Hong, Shaodong</au><au>Zhang, Li</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Pre-Treatment Tumor Growth Rate Predicts Clinical Outcomes of Patients With Advanced Non-Small Cell Lung Cancer Undergoing Anti-PD-1/PD-L1 Therapy</atitle><jtitle>Frontiers in oncology</jtitle><addtitle>Front Oncol</addtitle><date>2021-01-19</date><risdate>2021</risdate><volume>10</volume><spage>621329</spage><epage>621329</epage><pages>621329-621329</pages><issn>2234-943X</issn><eissn>2234-943X</eissn><abstract>Tumor growth rate (TGR; percent size change per month [%/m]) is postulated as an early radio-graphic predictor of response to anti-cancer treatment to overcome limitations of RECIST. We aimed to evaluate the predictive value of pre-treatment TGR (TGR
) for outcomes of advanced non-small cell lung cancer (aNSCLC) patients treated with anti-PD-1/PD-L1 monotherapy. We retrospectively screened all aNSCLC patients who received PD-1 axis inhibitors in Sun Yat-Sen University Cancer Center between August 2016 and June 2018. TGR
was calculated as the percentage change in tumor size per month (%/m) derived from two computed tomography (CT) scans during a "wash-out" period before the initiation of PD-1 axis inhibition. Final follow-up date was August 28, 2019. The X-tile program was used to identify the cut-off value of TGR
based on maximum progression-free survival (PFS) stratification. Patients were divided into two groups per the selected TGR
cut-off. The primary outcome was the difference of PFS between the two groups. The Kaplan-Meier methods and Cox regression models were performed for survival analysis. A total of 80 eligible patients were included (54 [67.5%] male; median [range] age, 55 [30-74] years). Median (range) TGR
was 21.1 (-33.7-246.0)%/m. The optimal cut-off value of TGR
was 25.3%/m. Patients with high TGR
had shorter median PFS (1.8 months; 95% CI, 1.6 - 2.1 months) than those with low TGR
(2.7 months; 95% CI, 0.5 - 4.9 months) (
= 0.005). Multivariate Cox regression analysis revealed that higher TGR
independently predicted inferior PFS (hazard ratio [HR] 1.97; 95% CI, 1.08-3.60;
= 0.026). Higher TGR
was also significantly associated with less durable clinical benefit rate (34.8% vs. 8.8%,
= 0.007). High pre-treatment TGR was a reliable predictor of inferior PFS and clinical benefit in aNSCLC patients undergoing anti-PD-1/PD-L1 monotherapy. The findings highlight the role of TGR
as an early biomarker to predict benefit from immunotherapy and could allow tailoring patient's follow-up.</abstract><cop>Switzerland</cop><pub>Frontiers Media S.A</pub><pmid>33552993</pmid><doi>10.3389/fonc.2020.621329</doi><tpages>1</tpages><oa>free_for_read</oa></addata></record> |
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subjects | anti-PD-1/PD-L1 therapy immunotherapy non-small cell lung cancer NSCLC Oncology progression-free survival tumor growth rate |
title | Pre-Treatment Tumor Growth Rate Predicts Clinical Outcomes of Patients With Advanced Non-Small Cell Lung Cancer Undergoing Anti-PD-1/PD-L1 Therapy |
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