Strong instrumental variables biased propensity scores in comparative effectiveness research: A case study in oncology
Some medications require specific medical procedures in the weeks before their start. Such procedures may meet the definition of instrumental variables (IVs). We examined how they may influence treatment effect estimation in propensity score (PS)-adjusted comparative studies, and how to remedy. Diff...
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| Veröffentlicht in: | Journal of clinical epidemiology 2023-03, Vol.155, p.31-38 |
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| creator | Thurin, Nicolas H. Jové, Jérémy Lassalle, Régis Rouyer, Magali Lamarque, Stéphanie Bosco-Levy, Pauline Segalas, Corentin Schneeweiss, Sebastian Blin, Patrick Droz-Perroteau, Cécile |
| description | Some medications require specific medical procedures in the weeks before their start. Such procedures may meet the definition of instrumental variables (IVs). We examined how they may influence treatment effect estimation in propensity score (PS)-adjusted comparative studies, and how to remedy.
Different covariate assessment periods (CAPs) did and did not include the month preceding treatment start were used to compute PS in the French claims database (Sytème National des Données de Santé-SNDS), and 1:1 match patients with metastatic castration resistant prostate cancer initiating abiraterone acetate or docetaxel. The 36-month survival was assessed.
Among 1, 213 docetaxel and 2, 442 abiraterone initiators, the PS distribution resulting from the CAP [-12; 0 months] distinctly separated populations (c = 0.93; 273 matched pairs). The CAPs [-12;-1 months] identified 765 pairs (c = 0.81). Strong docetaxel treatment predictors during the month before treatment start were implantable delivery systems (1% vs. 59%), which fulfilled IV conditions. The 36-month survival was not meaningfully different under the [-12; 0 months] CAP but differed by 10% points (38% vs. 28%) after excluding month −1.
In the setting of highly predictive pretreatment procedures, excluding the immediate pre-exposure time from the CAP will reduce the risk of including potential IVs in PS models and may reduce bias. |
| doi_str_mv | 10.1016/j.jclinepi.2023.01.002 |
| format | Article |
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Different covariate assessment periods (CAPs) did and did not include the month preceding treatment start were used to compute PS in the French claims database (Sytème National des Données de Santé-SNDS), and 1:1 match patients with metastatic castration resistant prostate cancer initiating abiraterone acetate or docetaxel. The 36-month survival was assessed.
Among 1, 213 docetaxel and 2, 442 abiraterone initiators, the PS distribution resulting from the CAP [-12; 0 months] distinctly separated populations (c = 0.93; 273 matched pairs). The CAPs [-12;-1 months] identified 765 pairs (c = 0.81). Strong docetaxel treatment predictors during the month before treatment start were implantable delivery systems (1% vs. 59%), which fulfilled IV conditions. The 36-month survival was not meaningfully different under the [-12; 0 months] CAP but differed by 10% points (38% vs. 28%) after excluding month −1.
In the setting of highly predictive pretreatment procedures, excluding the immediate pre-exposure time from the CAP will reduce the risk of including potential IVs in PS models and may reduce bias.</description><identifier>ISSN: 0895-4356</identifier><identifier>EISSN: 1878-5921</identifier><identifier>DOI: 10.1016/j.jclinepi.2023.01.002</identifier><identifier>PMID: 36657590</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><subject>Acetic acid ; Algorithms ; Bias ; Cancer therapies ; Case reports ; Castration ; Chemotherapy ; Cohort analysis ; Comparative Effectiveness Research ; Comparative studies ; Construction ; Docetaxel - therapeutic use ; Epidemiology ; Estimates ; Feature selection ; Health care policy ; Hospitals ; Humans ; Instrumental variables ; Laboratories ; Life Sciences ; Male ; Matching ; Metastases ; Metastasis ; Patients ; Pharmaceutical sciences ; Pharmacology ; Pharmacy ; Probability ; Propensity Score ; Prostate cancer ; Prostatic Neoplasms, Castration-Resistant - drug therapy ; Prostatic Neoplasms, Castration-Resistant - pathology ; Retrospective Studies ; Risk reduction ; Santé publique et épidémiologie ; SNDS ; Statistics ; Survival ; Taxoids - therapeutic use ; Treatment Outcome ; Variables</subject><ispartof>Journal of clinical epidemiology, 2023-03, Vol.155, p.31-38</ispartof><rights>2023 Elsevier Inc.</rights><rights>Copyright © 2023 Elsevier Inc. All rights reserved.</rights><rights>2023. Elsevier Inc.</rights><rights>Distributed under a Creative Commons Attribution 4.0 International License</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c425t-2f5d6e8c8cde20d4a36909ed620f45dd41c7526decb9b51b1f8ba0101c102c943</cites><orcidid>0000-0001-9763-5974 ; 0000-0003-2575-467X ; 0000-0001-6726-6215 ; 0000-0002-2560-4412 ; 0000-0003-4005-7928 ; 0000-0003-3589-0819 ; 0000-0002-6902-003X ; 0000-0002-7697-1167</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S0895435623000021$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>230,314,776,780,881,3537,27901,27902,65306</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/36657590$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink><backlink>$$Uhttps://hal.science/hal-03988528$$DView record in HAL$$Hfree_for_read</backlink></links><search><creatorcontrib>Thurin, Nicolas H.</creatorcontrib><creatorcontrib>Jové, Jérémy</creatorcontrib><creatorcontrib>Lassalle, Régis</creatorcontrib><creatorcontrib>Rouyer, Magali</creatorcontrib><creatorcontrib>Lamarque, Stéphanie</creatorcontrib><creatorcontrib>Bosco-Levy, Pauline</creatorcontrib><creatorcontrib>Segalas, Corentin</creatorcontrib><creatorcontrib>Schneeweiss, Sebastian</creatorcontrib><creatorcontrib>Blin, Patrick</creatorcontrib><creatorcontrib>Droz-Perroteau, Cécile</creatorcontrib><title>Strong instrumental variables biased propensity scores in comparative effectiveness research: A case study in oncology</title><title>Journal of clinical epidemiology</title><addtitle>J Clin Epidemiol</addtitle><description>Some medications require specific medical procedures in the weeks before their start. Such procedures may meet the definition of instrumental variables (IVs). We examined how they may influence treatment effect estimation in propensity score (PS)-adjusted comparative studies, and how to remedy.
Different covariate assessment periods (CAPs) did and did not include the month preceding treatment start were used to compute PS in the French claims database (Sytème National des Données de Santé-SNDS), and 1:1 match patients with metastatic castration resistant prostate cancer initiating abiraterone acetate or docetaxel. The 36-month survival was assessed.
Among 1, 213 docetaxel and 2, 442 abiraterone initiators, the PS distribution resulting from the CAP [-12; 0 months] distinctly separated populations (c = 0.93; 273 matched pairs). The CAPs [-12;-1 months] identified 765 pairs (c = 0.81). Strong docetaxel treatment predictors during the month before treatment start were implantable delivery systems (1% vs. 59%), which fulfilled IV conditions. The 36-month survival was not meaningfully different under the [-12; 0 months] CAP but differed by 10% points (38% vs. 28%) after excluding month −1.
In the setting of highly predictive pretreatment procedures, excluding the immediate pre-exposure time from the CAP will reduce the risk of including potential IVs in PS models and may reduce bias.</description><subject>Acetic acid</subject><subject>Algorithms</subject><subject>Bias</subject><subject>Cancer therapies</subject><subject>Case reports</subject><subject>Castration</subject><subject>Chemotherapy</subject><subject>Cohort analysis</subject><subject>Comparative Effectiveness Research</subject><subject>Comparative studies</subject><subject>Construction</subject><subject>Docetaxel - therapeutic use</subject><subject>Epidemiology</subject><subject>Estimates</subject><subject>Feature selection</subject><subject>Health care policy</subject><subject>Hospitals</subject><subject>Humans</subject><subject>Instrumental variables</subject><subject>Laboratories</subject><subject>Life Sciences</subject><subject>Male</subject><subject>Matching</subject><subject>Metastases</subject><subject>Metastasis</subject><subject>Patients</subject><subject>Pharmaceutical sciences</subject><subject>Pharmacology</subject><subject>Pharmacy</subject><subject>Probability</subject><subject>Propensity Score</subject><subject>Prostate cancer</subject><subject>Prostatic Neoplasms, Castration-Resistant - drug therapy</subject><subject>Prostatic Neoplasms, Castration-Resistant - pathology</subject><subject>Retrospective Studies</subject><subject>Risk reduction</subject><subject>Santé publique et épidémiologie</subject><subject>SNDS</subject><subject>Statistics</subject><subject>Survival</subject><subject>Taxoids - therapeutic use</subject><subject>Treatment Outcome</subject><subject>Variables</subject><issn>0895-4356</issn><issn>1878-5921</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>8G5</sourceid><sourceid>BENPR</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNqFkc1u1DAUhSMEokPhFSpLbGCR4dqJHYcVowpapJFYAGvLsW9aRxl7sJNI8_Z1NG0X3bCyZX_n3J9TFFcUthSo-DJsBzM6j0e3ZcCqLdAtAHtVbKhsZMlbRl8XG5AtL-uKi4viXUoDAG2g4W-Li0oI3vAWNsXye4rB3xHn0xTnA_pJj2TR0eluxEQ6pxNacozhiD656USSCTF_OE9MOBx11JNbkGDfo1lvHlMiGUAdzf1XsiMmG5A0zfa0aoI3YQx3p_fFm16PCT88npfF3x_f_1zflvtfNz-vd_vS1IxPJeu5FSiNNBYZ2FpXooUWrWDQ19zampqGM2HRdG3HaUd72WnICzIUmGnr6rL4fPa916M6RnfQ8aSCdup2t1frG1StlJzJhWb205nN0_6bMU3q4JLBcdQew5wUa4RkTNQUMvrxBTqEOfo8iWISmko0nK7FxZkyMaQUsX_ugIJaU1SDekpRrSkqoCqnmIVXj_Zzd0D7LHuKLQPfzgDm3S0Oo0rGoTdoXcw5KBvc_2o8ALBasp8</recordid><startdate>20230301</startdate><enddate>20230301</enddate><creator>Thurin, Nicolas H.</creator><creator>Jové, Jérémy</creator><creator>Lassalle, Régis</creator><creator>Rouyer, Magali</creator><creator>Lamarque, Stéphanie</creator><creator>Bosco-Levy, Pauline</creator><creator>Segalas, Corentin</creator><creator>Schneeweiss, Sebastian</creator><creator>Blin, Patrick</creator><creator>Droz-Perroteau, Cécile</creator><general>Elsevier Inc</general><general>Elsevier Limited</general><general>Elsevier</general><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>3V.</scope><scope>7QL</scope><scope>7QP</scope><scope>7RV</scope><scope>7T2</scope><scope>7T7</scope><scope>7TK</scope><scope>7U7</scope><scope>7U9</scope><scope>7X7</scope><scope>7XB</scope><scope>88C</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>H94</scope><scope>K9.</scope><scope>KB0</scope><scope>M0S</scope><scope>M0T</scope><scope>M1P</scope><scope>M2O</scope><scope>M7N</scope><scope>MBDVC</scope><scope>NAPCQ</scope><scope>P64</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>Q9U</scope><scope>7X8</scope><scope>1XC</scope><scope>VOOES</scope><orcidid>https://orcid.org/0000-0001-9763-5974</orcidid><orcidid>https://orcid.org/0000-0003-2575-467X</orcidid><orcidid>https://orcid.org/0000-0001-6726-6215</orcidid><orcidid>https://orcid.org/0000-0002-2560-4412</orcidid><orcidid>https://orcid.org/0000-0003-4005-7928</orcidid><orcidid>https://orcid.org/0000-0003-3589-0819</orcidid><orcidid>https://orcid.org/0000-0002-6902-003X</orcidid><orcidid>https://orcid.org/0000-0002-7697-1167</orcidid></search><sort><creationdate>20230301</creationdate><title>Strong instrumental variables biased propensity scores in comparative effectiveness research: A case study in oncology</title><author>Thurin, Nicolas H. ; Jové, Jérémy ; Lassalle, Régis ; Rouyer, Magali ; Lamarque, Stéphanie ; Bosco-Levy, Pauline ; Segalas, Corentin ; Schneeweiss, Sebastian ; Blin, Patrick ; Droz-Perroteau, Cécile</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c425t-2f5d6e8c8cde20d4a36909ed620f45dd41c7526decb9b51b1f8ba0101c102c943</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Acetic acid</topic><topic>Algorithms</topic><topic>Bias</topic><topic>Cancer therapies</topic><topic>Case reports</topic><topic>Castration</topic><topic>Chemotherapy</topic><topic>Cohort analysis</topic><topic>Comparative Effectiveness Research</topic><topic>Comparative studies</topic><topic>Construction</topic><topic>Docetaxel - 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Academic</collection><collection>Hyper Article en Ligne (HAL)</collection><collection>Hyper Article en Ligne (HAL) (Open Access)</collection><jtitle>Journal of clinical epidemiology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Thurin, Nicolas H.</au><au>Jové, Jérémy</au><au>Lassalle, Régis</au><au>Rouyer, Magali</au><au>Lamarque, Stéphanie</au><au>Bosco-Levy, Pauline</au><au>Segalas, Corentin</au><au>Schneeweiss, Sebastian</au><au>Blin, Patrick</au><au>Droz-Perroteau, Cécile</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Strong instrumental variables biased propensity scores in comparative effectiveness research: A case study in oncology</atitle><jtitle>Journal of clinical epidemiology</jtitle><addtitle>J Clin Epidemiol</addtitle><date>2023-03-01</date><risdate>2023</risdate><volume>155</volume><spage>31</spage><epage>38</epage><pages>31-38</pages><issn>0895-4356</issn><eissn>1878-5921</eissn><abstract>Some medications require specific medical procedures in the weeks before their start. Such procedures may meet the definition of instrumental variables (IVs). We examined how they may influence treatment effect estimation in propensity score (PS)-adjusted comparative studies, and how to remedy.
Different covariate assessment periods (CAPs) did and did not include the month preceding treatment start were used to compute PS in the French claims database (Sytème National des Données de Santé-SNDS), and 1:1 match patients with metastatic castration resistant prostate cancer initiating abiraterone acetate or docetaxel. The 36-month survival was assessed.
Among 1, 213 docetaxel and 2, 442 abiraterone initiators, the PS distribution resulting from the CAP [-12; 0 months] distinctly separated populations (c = 0.93; 273 matched pairs). The CAPs [-12;-1 months] identified 765 pairs (c = 0.81). Strong docetaxel treatment predictors during the month before treatment start were implantable delivery systems (1% vs. 59%), which fulfilled IV conditions. The 36-month survival was not meaningfully different under the [-12; 0 months] CAP but differed by 10% points (38% vs. 28%) after excluding month −1.
In the setting of highly predictive pretreatment procedures, excluding the immediate pre-exposure time from the CAP will reduce the risk of including potential IVs in PS models and may reduce bias.</abstract><cop>United States</cop><pub>Elsevier Inc</pub><pmid>36657590</pmid><doi>10.1016/j.jclinepi.2023.01.002</doi><tpages>8</tpages><orcidid>https://orcid.org/0000-0001-9763-5974</orcidid><orcidid>https://orcid.org/0000-0003-2575-467X</orcidid><orcidid>https://orcid.org/0000-0001-6726-6215</orcidid><orcidid>https://orcid.org/0000-0002-2560-4412</orcidid><orcidid>https://orcid.org/0000-0003-4005-7928</orcidid><orcidid>https://orcid.org/0000-0003-3589-0819</orcidid><orcidid>https://orcid.org/0000-0002-6902-003X</orcidid><orcidid>https://orcid.org/0000-0002-7697-1167</orcidid><oa>free_for_read</oa></addata></record> |
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| ispartof | Journal of clinical epidemiology, 2023-03, Vol.155, p.31-38 |
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| source | MEDLINE; Elsevier ScienceDirect Journals |
| subjects | Acetic acid Algorithms Bias Cancer therapies Case reports Castration Chemotherapy Cohort analysis Comparative Effectiveness Research Comparative studies Construction Docetaxel - therapeutic use Epidemiology Estimates Feature selection Health care policy Hospitals Humans Instrumental variables Laboratories Life Sciences Male Matching Metastases Metastasis Patients Pharmaceutical sciences Pharmacology Pharmacy Probability Propensity Score Prostate cancer Prostatic Neoplasms, Castration-Resistant - drug therapy Prostatic Neoplasms, Castration-Resistant - pathology Retrospective Studies Risk reduction Santé publique et épidémiologie SNDS Statistics Survival Taxoids - therapeutic use Treatment Outcome Variables |
| title | Strong instrumental variables biased propensity scores in comparative effectiveness research: A case study in oncology |
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