{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,18]],"date-time":"2026-08-18T00:42:56Z","timestamp":1787013776487,"version":"build-2736575974"},"reference-count":26,"publisher":"Wiley","issue":"10","license":[{"start":{"date-parts":[[2014,10,23]],"date-time":"2014-10-23T00:00:00Z","timestamp":1414022400000},"content-version":"vor","delay-in-days":22,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"funder":[{"DOI":"10.13039\/100000027","name":"National Institute on Alcohol Abuse and Alcoholism","doi-asserted-by":"publisher","award":["RO1AA017173"],"award-info":[{"award-number":["RO1AA017173"]}],"id":[{"id":"10.13039\/100000027","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000027","name":"National Institute on Alcohol Abuse and Alcoholism","doi-asserted-by":"publisher","award":["K05AA014715"],"award-info":[{"award-number":["K05AA014715"]}],"id":[{"id":"10.13039\/100000027","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000027","name":"National Institute on Alcohol Abuse and Alcoholism","doi-asserted-by":"publisher","award":["K23AA020000"],"award-info":[{"award-number":["K23AA020000"]}],"id":[{"id":"10.13039\/100000027","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Alcoholism Clin &amp;amp; Exp Res"],"published-print":{"date-parts":[[2014,10]]},"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>\n                      The goal of the current study was to use tree\u2010based methods (\n                      <jats:styled-content style=\"fixed-case\">Z<\/jats:styled-content>\n                      hang and\n                      <jats:styled-content style=\"fixed-case\">S<\/jats:styled-content>\n                      inger, 2010,\n                      <jats:italic>Recursive Partitioning and Applications<\/jats:italic>\n                      , 2nd ed.\n                      <jats:styled-content style=\"fixed-case\">S<\/jats:styled-content>\n                      pringer,\n                      <jats:styled-content style=\"fixed-case\">N<\/jats:styled-content>\n                      ew\n                      <jats:styled-content style=\"fixed-case\">Y<\/jats:styled-content>\n                      ork) to identify predictors of abstinence from heavy drinking in\n                      <jats:styled-content style=\"fixed-case\">COMBINE<\/jats:styled-content>\n                      (\n                      <jats:styled-content style=\"fixed-case\">A<\/jats:styled-content>\n                      nton et\u00a0al.\n                      <jats:italic>JAMA<\/jats:italic>\n                      2006; 295:2003), the largest study of pharmacotherapy for alcoholism in the\n                      <jats:styled-content style=\"fixed-case\">U<\/jats:styled-content>\n                      nited\n                      <jats:styled-content style=\"fixed-case\">S<\/jats:styled-content>\n                      tates to date, and to validate these results in\n                      <jats:styled-content style=\"fixed-case\">PREDICT<\/jats:styled-content>\n                      (Mann et\u00a0al.\n                      <jats:italic>Addict Biol<\/jats:italic>\n                      2012; 18:937), a parallel study conducted in\n                      <jats:styled-content style=\"fixed-case\">G<\/jats:styled-content>\n                      ermany.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      We compared a classification tree constructed according to purely statistical criteria to a tree constructed according to a combination of statistical criteria and clinical considerations for prediction of no heavy drinking during treatment in\n                      <jats:styled-content style=\"fixed-case\">COMBINE<\/jats:styled-content>\n                      . We considered over 100 baseline predictors. The tree approach was compared to logistic regression. The trees and a deterministic forest identified the most important predictors of no heavy drinking for direct testing in\n                      <jats:styled-content style=\"fixed-case\">PREDICT<\/jats:styled-content>\n                      .\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      The tree built using both clinical and statistical considerations consisted of 4 splits based on consecutive days of abstinence (\n                      <jats:styled-content style=\"fixed-case\">CDA<\/jats:styled-content>\n                      ) prior to randomization, age, family history of alcoholism, and confidence to resist drinking in response to withdrawal and urges. The tree based on statistical considerations with 4 splits also split on\n                      <jats:styled-content style=\"fixed-case\">CDA<\/jats:styled-content>\n                      and age but also on gamma\u2010glutamyl transferase level and drinking goal. Deterministic forest identified\n                      <jats:styled-content style=\"fixed-case\">CDA<\/jats:styled-content>\n                      , age, and drinking goal as the most important predictors. Backward elimination logistic regression among the top 18 predictors identified in the deterministic forest analyses identified only age and\n                      <jats:styled-content style=\"fixed-case\">CDA<\/jats:styled-content>\n                      as significant main effects. Longer\n                      <jats:styled-content style=\"fixed-case\">CDA<\/jats:styled-content>\n                      and goal of complete abstinence were associated with better outcomes in both data sets.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>\n                      The most reliable predictors of abstinence from heavy drinking were\n                      <jats:styled-content style=\"fixed-case\">CDA<\/jats:styled-content>\n                      and drinking goal. Trees provide binary decision rules and straightforward graphical representations for identification of subgroups based on response and may be easier to implement in clinical settings.\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/acer.12541","type":"journal-article","created":{"date-parts":[[2014,10,30]],"date-time":"2014-10-30T06:12:18Z","timestamp":1414649538000},"page":"2647-2656","source":"Crossref","is-referenced-by-count":18,"title":["Predictors of Abstinence from Heavy Drinking During Treatment in\n                    <scp>COMBINE<\/scp>\n                    and External Validation in\n                    <scp>PREDICT<\/scp>"],"prefix":"10.1111","volume":"38","author":[{"given":"Ralitza","family":"Gueorguieva","sequence":"first","affiliation":[{"name":"Department of Biostatistics Yale University School of Public Health and School of Medicine New Haven 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