{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,7]],"date-time":"2026-10-07T21:33:21Z","timestamp":1791408801764,"version":"4.3.3"},"reference-count":26,"publisher":"BMJ","issue":"2","license":[{"start":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T00:00:00Z","timestamp":1772064000000},"content-version":"unspecified","delay-in-days":25,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":["bmj.com"],"crossmark-restriction":true},"short-container-title":["BMJ Open"],"accepted":{"date-parts":[[2026,2,13]]},"published-print":{"date-parts":[[2026,2]]},"abstract":"<jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>To use best practices in pharmacoepidemiology to assess the association between new use of brain-penetrant calcium channel blockers (BP-CCBs) compared with use of non-brain-penetrant CCBs (NP-CCBs) and the incidence of neuropsychiatric outcomes.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Design<\/jats:title>\n                    <jats:p>Retrospective comparative cohort study.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Setting<\/jats:title>\n                    <jats:p>Secondary data from nine claims and electronic health record databases from across the globe were used.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Participants<\/jats:title>\n                    <jats:p>First use of a CCB was the index date. There were 1.2\u2009million BP-CCB patients and 9.3\u2009million NP-CCB patients identified across all databases, with 881\u2009758 matched in each group.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Interventions<\/jats:title>\n                    <jats:p>Patients were categorised as either initiating BP-CCBs or NP-CCBs. On-treatment and intention-to-treat analyses were conducted. Large-scale propensity models were used to match cohorts and control for observed confounding. Cox models were used to analyse the time to incident neuropsychiatric disorders. Negative control outcomes were used to calibrate estimates, CIs and p values to account for residual confounding. Diagnostics were used to assess the validity of the analysis.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Primary and secondary outcome measures<\/jats:title>\n                    <jats:p>The time to first diagnosis of schizophrenia, schizoaffective disorder, major depressive disorder (MDD) and bipolar disorder was assessed independently. HRs compared the BP-CCB group to the NP-CCB group.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>For the outcome of incident MDD in the intention-to-treat design, the meta-analytic HR (95%\u2009CI) was 1.02 (0.97, 1.08). Meta-analytic HRs for bipolar disorder (1.04 (0.96, 1.13)), schizophrenia (1.05 (0.94, 1.18)) and schizoaffective disorder (1.04 (0.87, 1.23)) showed similar null effects. The on-treatment analysis was largely consistent: MDD (1.01 (0.96, 1.06)), bipolar (1.05 (0.86, 1.27)), schizophrenia (1.09 (0.87, 1.38)) and schizoaffective (1.00 (0.71, 1.40)).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>There was no evidence of an association with any of the neuropsychiatric conditions of interest between use of BP-CCB and NP-CCB. This does not rule out the potential beneficial effect of CCB formulations and doses targeted specifically for the brain rather than the cardiovascular system.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1136\/bmjopen-2025-100282","type":"journal-article","created":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T14:15:16Z","timestamp":1772115316000},"page":"e100282","update-policy":"https:\/\/doi.org\/10.1136\/crossmarkpolicy","source":"Crossref","is-referenced-by-count":2,"title":["Lack of association between the brain penetrance of calcium channel blockers and the incidence of neuropsychiatric outcomes: a retrospective, multidatabase cohort study"],"prefix":"10.1136","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5417-3925","authenticated-orcid":false,"given":"David M","family":"Kern","sequence":"first","affiliation":[{"name":"Global Epidemiology Organization, Johnson & Johnson, Horsham, Pennsylvania, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Justin","family":"Bohn","sequence":"additional","affiliation":[{"name":"Global Epidemiology Organization, Johnson & Johnson, Washington, District of Columbia, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michael P","family":"Maher","sequence":"additional","affiliation":[{"name":"Neuroscience, Johnson & Johnson, La Jolla, California, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dmytro","family":"Dymshyts","sequence":"additional","affiliation":[{"name":"Global Epidemiology Organization, Johnson & Johnson, Madrid, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Azza","family":"Shoaibi","sequence":"additional","affiliation":[{"name":"Global Epidemiology Organization, Johnson & Johnson, Titusville, New Jersey, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"239","published-online":{"date-parts":[[2026,2,26]]},"reference":[{"key":"2026022606150610000_16.2.e100282.1","doi-asserted-by":"publisher","DOI":"10.1007\/164_2022_624"},{"key":"2026022606150610000_16.2.e100282.2","doi-asserted-by":"publisher","DOI":"10.1038\/nature13595"},{"key":"2026022606150610000_16.2.e100282.3","doi-asserted-by":"publisher","DOI":"10.1016\/s0140-6736(12)62129-1"},{"key":"2026022606150610000_16.2.e100282.4","doi-asserted-by":"publisher","DOI":"10.1016\/j.pneurobio.2015.09.002"},{"key":"2026022606150610000_16.2.e100282.5","doi-asserted-by":"publisher","DOI":"10.1016\/j.pneurobio.2012.06.001"},{"key":"2026022606150610000_16.2.e100282.6","doi-asserted-by":"publisher","DOI":"10.1007\/s13311-017-0532-0"},{"key":"2026022606150610000_16.2.e100282.7","doi-asserted-by":"publisher","DOI":"10.1016\/j.celrep.2014.10.015"},{"key":"2026022606150610000_16.2.e100282.8","doi-asserted-by":"publisher","DOI":"10.1038\/mp.2013.107"},{"key":"2026022606150610000_16.2.e100282.9","doi-asserted-by":"publisher","DOI":"10.1038\/mp.2016.86"},{"key":"2026022606150610000_16.2.e100282.10","doi-asserted-by":"publisher","DOI":"10.1038\/s41380-022-01615-6"},{"key":"2026022606150610000_16.2.e100282.11","doi-asserted-by":"publisher","DOI":"10.1177\/1062860606288243"},{"key":"2026022606150610000_16.2.e100282.12","doi-asserted-by":"publisher","DOI":"10.1176\/appi.ajp.2014.14030423"},{"key":"2026022606150610000_16.2.e100282.13","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbi.2022.104204"},{"key":"2026022606150610000_16.2.e100282.14","doi-asserted-by":"crossref","first-page":"2005","DOI":"10.1093\/ije\/dyy120","article-title":"Evaluating large-scale propensity score performance through real-world and synthetic data experiments","volume":"47","author":"Tian","year":"2018","journal-title":"Int J Epidemiol"},{"key":"2026022606150610000_16.2.e100282.15","doi-asserted-by":"crossref","first-page":"1218","DOI":"10.1002\/pds.1674","article-title":"Assessing balance in measured baseline covariates when using many\u2010to\u2010one matching on the propensity\u2010score","volume":"17","author":"Austin","year":"2008","journal-title":"Pharmacoepidemiology and Drug"},{"key":"2026022606150610000_16.2.e100282.16","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1708282114"},{"key":"2026022606150610000_16.2.e100282.17","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbi.2016.12.005"},{"key":"2026022606150610000_16.2.e100282.18","doi-asserted-by":"crossref","first-page":"438","DOI":"10.1177\/09622802211060518","article-title":"Combining cox regressions across a heterogeneous distributed research network facing small and zero counts","volume":"31","author":"Schuemie","year":"2022","journal-title":"Stat Methods Med Res"},{"key":"2026022606150610000_16.2.e100282.19","doi-asserted-by":"publisher","DOI":"10.2105\/AJPH.2004.059204"},{"key":"2026022606150610000_16.2.e100282.20","doi-asserted-by":"publisher","DOI":"10.1177\/003591576505800503"},{"key":"2026022606150610000_16.2.e100282.21","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1002\/pds.5547","article-title":"Core concepts in pharmacoepidemiology: Key biases arising in pharmacoepidemiologic studies","volume":"32","author":"Acton","year":"2023","journal-title":"Pharmacoepidemiology and Drug"},{"key":"2026022606150610000_16.2.e100282.22","unstructured":"National Institute of Mental Health . Schizophrenia. 2024. Available: https:\/\/www.nimh.nih.gov\/health\/statistics\/schizophrenia"},{"key":"2026022606150610000_16.2.e100282.23","doi-asserted-by":"crossref","first-page":"1261","DOI":"10.1093\/gerona\/glab373","article-title":"Validation of Claims Algorithms to Identify Alzheimer\u2019s Disease and Related Dementias","volume":"77","author":"McCarthy","year":"2022","journal-title":"J Gerontol A Biol Sci Med Sci"},{"key":"2026022606150610000_16.2.e100282.24","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1176\/ps.43.1.69","article-title":"Accuracy of Diagnoses of Schizophrenia in Medicaid Claims","volume":"43","author":"Lurie","year":"1992","journal-title":"PS"},{"key":"2026022606150610000_16.2.e100282.25","doi-asserted-by":"crossref","unstructured":"Doktorchik C , Patten S , Eastwood C , et al . Validation of a case definition for depression in administrative data against primary chart data as a reference standard. BMC Psychiatry 2019;19. doi:10.1186\/s12888-018-1990-6","DOI":"10.1186\/s12888-018-1990-6"},{"key":"2026022606150610000_16.2.e100282.26","doi-asserted-by":"crossref","first-page":"154","DOI":"10.1176\/appi.ajp.2016.16010077","article-title":"Predicting Suicidal Behavior From Longitudinal Electronic Health Records","volume":"174","author":"Barak-Corren","year":"2017","journal-title":"AJP"}],"container-title":["BMJ Open"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/syndication.highwire.org\/content\/doi\/10.1136\/bmjopen-2025-100282","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T14:15:19Z","timestamp":1772115319000},"score":1,"resource":{"primary":{"URL":"https:\/\/bmjopen.bmj.com\/lookup\/doi\/10.1136\/bmjopen-2025-100282"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,2]]},"references-count":26,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2026,2,26]]},"published-print":{"date-parts":[[2026,2]]}},"alternative-id":["10.1136\/bmjopen-2025-100282"],"URL":"https:\/\/doi.org\/10.1136\/bmjopen-2025-100282","relation":{},"ISSN":["2044-6055","2044-6055"],"issn-type":[{"value":"2044-6055","type":"print"},{"value":"2044-6055","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,2]]}}}