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Efthimiou O, Hoogland J, Debray TP, Seo M, Furukawa TA, Egger M, White IR. Measuring the performance of prediction models to personalize treatment choice. Stat Med 2023; 42:1188-1206. [PMID: 36700492 PMCID: PMC7615726 DOI: 10.1002/sim.9665] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Revised: 11/07/2022] [Accepted: 12/31/2022] [Indexed: 01/27/2023]
Abstract
When data are available from individual patients receiving either a treatment or a control intervention in a randomized trial, various statistical and machine learning methods can be used to develop models for predicting future outcomes under the two conditions, and thus to predict treatment effect at the patient level. These predictions can subsequently guide personalized treatment choices. Although several methods for validating prediction models are available, little attention has been given to measuring the performance of predictions of personalized treatment effect. In this article, we propose a range of measures that can be used to this end. We start by defining two dimensions of model accuracy for treatment effects, for a single outcome: discrimination for benefit and calibration for benefit. We then amalgamate these two dimensions into an additional concept, decision accuracy, which quantifies the model's ability to identify patients for whom the benefit from treatment exceeds a given threshold. Subsequently, we propose a series of performance measures related to these dimensions and discuss estimating procedures, focusing on randomized data. Our methods are applicable for continuous or binary outcomes, for any type of prediction model, as long as it uses baseline covariates to predict outcomes under treatment and control. We illustrate all methods using two simulated datasets and a real dataset from a trial in depression. We implement all methods in the R package predieval. Results suggest that the proposed measures can be useful in evaluating and comparing the performance of competing models in predicting individualized treatment effect.
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Affiliation(s)
- Orestis Efthimiou
- Institute of Social and Preventive Medicine (ISPM), University of BernBernSwitzerland
- Institute of Primary Health Care (BIHAM), University of BernBernSwitzerland
- Department of PsychiatryUniversity of OxfordOxfordUK
| | - Jeroen Hoogland
- Julius Center for Health Sciences and Primary CareUniversity Medical Center Utrecht, Utrecht UniversityUtrechtThe Netherlands
- Department of Epidemiology and Data ScienceAmsterdam University Medical CentersAmsterdamThe Netherlands
| | - Thomas P.A. Debray
- Julius Center for Health Sciences and Primary CareUniversity Medical Center Utrecht, Utrecht UniversityUtrechtThe Netherlands
- Smart Data Analysis and Statistics B.V.UtrechtThe Netherlands
| | - Michael Seo
- Institute of Social and Preventive Medicine (ISPM), University of BernBernSwitzerland
- Graduate School for Health SciencesUniversity of BernBernSwitzerland
| | - Toshiaki A. Furukawa
- Departments of Health Promotion and Human Behavior and of Clinical EpidemiologyKyoto University Graduate School of Medicine/School of Public HealthKyotoJapan
| | - Matthias Egger
- Institute of Social and Preventive Medicine (ISPM), University of BernBernSwitzerland
- Centre for Infectious Disease Epidemiology and Research, Faculty of Health SciencesUniversity of Cape TownCape TownSouth Africa
- Population Health Sciences, Bristol Medical SchoolUniversity of BristolBristolUK
| | - Ian R. White
- MRC Clinical Trials Unit at UCLUniversity College LondonLondonUK
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Zhu Y, Wu Z, Zhao D, Wu X, He R, Wang Z, Peng D, Fang Y. Clinical Guideline (CANMAT 2016) Discordance of Medications for Patients with Major Depressive Disorder in China. Neuropsychiatr Dis Treat 2023; 19:829-839. [PMID: 37077710 PMCID: PMC10106790 DOI: 10.2147/ndt.s401359] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Accepted: 03/23/2023] [Indexed: 04/21/2023] Open
Abstract
Objective This survey aims to explore the current medical treatment of major depressive disorder (MDD) in China and match its degree with Canadian Network for Mood and Anxiety Treatments (CANMAT). Methods A total of 3275 patients were recruited from 16 mental health centers and 16 general hospitals in China. Descriptive statistics presented the total number and percentage of drugs, as well as all kinds of treatments. Results Selective serotonin reuptake inhibitors (SSRIs) accounted for the largest proportion (57.2%), followed by serotonin-noradrenaline reuptake inhibitors (SNRIs) (22.8%) and mirtazapine (7.0%) in the first therapy, while that of SNRIs (53.9%) followed by SSRIs (39.2%) and mirtazapine (9.8%) in the follow-up therapy. An average of 1.85 medications was administered to each MDD patient. Conclusion SSRIs were the first choice in the first therapy, while the proportion of those drugs decreased during the follow-up therapy and were replaced by SNRIs. Plenty of combined pharmacotherapies were directly selected as the first trial of patients, which was inconsistent with guideline recommendations.
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Affiliation(s)
- Yuncheng Zhu
- Division of Mood Disorders, Shanghai Hongkou Mental Health Center, Shanghai, People’s Republic of China
- Clinical Research Center & Division of Mood Disorders, Shanghai Mental Health Center, Shanghai JiaoTong University School of Medicine, Shanghai, People’s Republic of China
- Clinical Research Center for Mental Health, School of Medicine, Shanghai University, Shanghai, People's Republic of China
| | - Zhiguo Wu
- Clinical Research Center in Mental Health, Shanghai Yangpu District Mental Health Center, Shanghai University of Medicine & Health Sciences, Shanghai, People's Republic of China
| | - Dongmei Zhao
- Division of Psychiatry, Shanghai Changning Mental Health Center, Shanghai, People’s Republic of China
| | - Xiaohui Wu
- Clinical Research Center & Division of Mood Disorders, Shanghai Mental Health Center, Shanghai JiaoTong University School of Medicine, Shanghai, People’s Republic of China
| | | | - Zuowei Wang
- Division of Mood Disorders, Shanghai Hongkou Mental Health Center, Shanghai, People’s Republic of China
- Clinical Research Center for Mental Health, School of Medicine, Shanghai University, Shanghai, People's Republic of China
| | - Daihui Peng
- Clinical Research Center & Division of Mood Disorders, Shanghai Mental Health Center, Shanghai JiaoTong University School of Medicine, Shanghai, People’s Republic of China
| | - Yiru Fang
- Clinical Research Center & Division of Mood Disorders, Shanghai Mental Health Center, Shanghai JiaoTong University School of Medicine, Shanghai, People’s Republic of China
- Department of Psychiatry & Affective Disorders Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
- CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai, People’s Republic of China
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai, People’s Republic of China
- Correspondence: Yiru Fang, Email
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Davies P, Ijaz S, Williams CJ, Kessler D, Lewis G, Wiles N. Pharmacological interventions for treatment-resistant depression in adults. Cochrane Database Syst Rev 2019; 12:CD010557. [PMID: 31846068 PMCID: PMC6916711 DOI: 10.1002/14651858.cd010557.pub2] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
BACKGROUND Although antidepressants are often a first-line treatment for adults with moderate to severe depression, many people do not respond adequately to medication, and are said to have treatment-resistant depression (TRD). Little evidence exists to inform the most appropriate 'next step' treatment for these people. OBJECTIVES To assess the effectiveness of standard pharmacological treatments for adults with TRD. SEARCH METHODS We searched the Cochrane Common Mental Disorders Controlled Trials Register (CCMDCTR) (March 2016), CENTRAL, MEDLINE, Embase, PsycINFO and Web of Science (31 December 2018), the World Health Organization trials portal and ClinicalTrials.gov for unpublished and ongoing studies, and screened bibliographies of included studies and relevant systematic reviews without date or language restrictions. SELECTION CRITERIA Randomised controlled trials (RCTs) with participants aged 18 to 74 years with unipolar depression (based on criteria from DSM-IV-TR or earlier versions, International Classification of Diseases (ICD)-10, Feighner criteria or Research Diagnostic Criteria) who had not responded to a minimum of four weeks of antidepressant treatment at a recommended dose. Interventions were: (1) increasing the dose of antidepressant monotherapy; (2) switching to a different antidepressant monotherapy; (3) augmenting treatment with another antidepressant; (4) augmenting treatment with a non-antidepressant. All were compared with continuing antidepressant monotherapy. We excluded studies of non-standard pharmacological treatments (e.g. sex hormones, vitamins, herbal medicines and food supplements). DATA COLLECTION AND ANALYSIS Two reviewers used standard Cochrane methods to extract data, assess risk of bias, and resolve disagreements. We analysed continuous outcomes with mean difference (MD) or standardised mean difference (SMD) and 95% confidence interval (CI). For dichotomous outcomes, we calculated a relative risk (RR) and 95% CI. Where sufficient data existed, we conducted meta-analyses using random-effects models. MAIN RESULTS We included 10 RCTs (2731 participants). Nine were conducted in outpatient settings and one in both in- and outpatients. Mean age of participants ranged from 42 - 50.2 years, and most were female. One study investigated switching to, or augmenting current antidepressant treatment with, another antidepressant (mianserin). Another augmented current antidepressant treatment with the antidepressant mirtazapine. Eight studies augmented current antidepressant treatment with a non-antidepressant (either an anxiolytic (buspirone) or an antipsychotic (cariprazine; olanzapine; quetiapine (3 studies); or ziprasidone (2 studies)). We judged most studies to be at a low or unclear risk of bias. Only one of the included studies was not industry-sponsored. There was no evidence of a difference in depression severity when current treatment was switched to mianserin (MD on Hamilton Rating Scale for Depression (HAM-D) = -1.8, 95% CI -5.22 to 1.62, low-quality evidence)) compared with continuing on antidepressant monotherapy. Nor was there evidence of a difference in numbers dropping out of treatment (RR 2.08, 95% CI 0.94 to 4.59, low-quality evidence; dropouts 38% in the mianserin switch group; 18% in the control). Augmenting current antidepressant treatment with mianserin was associated with an improvement in depression symptoms severity scores from baseline (MD on HAM-D -4.8, 95% CI -8.18 to -1.42; moderate-quality evidence). There was no evidence of a difference in numbers dropping out (RR 1.02, 95% CI 0.38 to 2.72; low-quality evidence; 19% dropouts in the mianserin-augmented group; 38% in the control). When current antidepressant treatment was augmented with mirtazapine, there was little difference in depressive symptoms (MD on Beck Depression Inventory (BDI-II) -1.7, 95% CI -4.03 to 0.63; high-quality evidence) and no evidence of a difference in dropout numbers (RR 0.50, 95% CI 0.15 to 1.62; dropouts 2% in mirtazapine-augmented group; 3% in the control). Augmentation with buspirone provided no evidence of a benefit in terms of a reduction in depressive symptoms (MD on Montgomery and Asberg Depression Rating Scale (MADRS) -0.30, 95% CI -9.48 to 8.88; low-quality evidence) or numbers of drop-outs (RR 0.60, 95% CI 0.23 to 1.53; low-quality evidence; dropouts 11% in buspirone-augmented group; 19% in the control). Severity of depressive symptoms reduced when current treatment was augmented with cariprazine (MD on MADRS -1.50, 95% CI -2.74 to -0.25; high-quality evidence), olanzapine (MD on HAM-D -7.9, 95% CI -16.76 to 0.96; low-quality evidence; MD on MADRS -12.4, 95% CI -22.44 to -2.36; low-quality evidence), quetiapine (SMD -0.32, 95% CI -0.46 to -0.18; I2 = 6%, high-quality evidence), or ziprasidone (MD on HAM-D -2.73, 95% CI -4.53 to -0.93; I2 = 0, moderate-quality evidence) compared with continuing on antidepressant monotherapy. However, a greater number of participants dropped out when antidepressant monotherapy was augmented with an antipsychotic (cariprazine RR 1.68, 95% CI 1.16 to 2.41; quetiapine RR 1.57, 95% CI: 1.14 to 2.17; ziprasidone RR 1.60, 95% CI 1.01 to 2.55) compared with antidepressant monotherapy, although estimates for olanzapine augmentation were imprecise (RR 0.33, 95% CI 0.04 to 2.69). Dropout rates ranged from 10% to 39% in the groups augmented with an antipsychotic, and from 12% to 23% in the comparison groups. The most common reasons for dropping out were side effects or adverse events. We also summarised data about response and remission rates (based on changes in depressive symptoms) for included studies, along with data on social adjustment and social functioning, quality of life, economic outcomes and adverse events. AUTHORS' CONCLUSIONS A small body of evidence shows that augmenting current antidepressant therapy with mianserin or with an antipsychotic (cariprazine, olanzapine, quetiapine or ziprasidone) improves depressive symptoms over the short-term (8 to 12 weeks). However, this evidence is mostly of low or moderate quality due to imprecision of the estimates of effects. Improvements with antipsychotics need to be balanced against the increased likelihood of dropping out of treatment or experiencing an adverse event. Augmentation of current antidepressant therapy with a second antidepressant, mirtazapine, does not produce a clinically important benefit in reduction of depressive symptoms (high-quality evidence). The evidence regarding the effects of augmenting current antidepressant therapy with buspirone or switching current antidepressant treatment to mianserin is currently insufficient. Further trials are needed to increase the certainty of these findings and to examine long-term effects of treatment, as well as the effectiveness of other pharmacological treatment strategies.
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Affiliation(s)
- Philippa Davies
- University of BristolPopulation Health Sciences, Bristol Medical SchoolCanynge HallBristolUKBS8 2PS
- University Hospitals Bristol NHS Foundation TrustNIHR ARC WestBristolUK
| | - Sharea Ijaz
- University of BristolPopulation Health Sciences, Bristol Medical SchoolCanynge HallBristolUKBS8 2PS
- University Hospitals Bristol NHS Foundation TrustNIHR ARC WestBristolUK
| | - Catherine J Williams
- University of BristolSchool of Social and Community Medicine39 Whatley RoadBristolUKBS8 2PS
| | - David Kessler
- University of BristolPopulation Health Sciences, Bristol Medical SchoolCanynge HallBristolUKBS8 2PS
| | - Glyn Lewis
- UCLUCL Division of Psychiatry67‐73 Riding House StLondonUKW1W 7EJ
| | - Nicola Wiles
- University of BristolPopulation Health Sciences, Bristol Medical SchoolCanynge HallBristolUKBS8 2PS
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Kato T, Furukawa TA, Mantani A, Kurata K, Kubouchi H, Hirota S, Sato H, Sugishita K, Chino B, Itoh K, Ikeda Y, Shinagawa Y, Kondo M, Okamoto Y, Fujita H, Suga M, Yasumoto S, Tsujino N, Inoue T, Fujise N, Akechi T, Yamada M, Shimodera S, Watanabe N, Inagaki M, Miki K, Ogawa Y, Takeshima N, Hayasaka Y, Tajika A, Shinohara K, Yonemoto N, Tanaka S, Zhou Q, Guyatt GH. Optimising first- and second-line treatment strategies for untreated major depressive disorder - the SUN☺D study: a pragmatic, multi-centre, assessor-blinded randomised controlled trial. BMC Med 2018; 16:103. [PMID: 29991347 PMCID: PMC6040068 DOI: 10.1186/s12916-018-1096-5] [Citation(s) in RCA: 46] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/08/2017] [Accepted: 06/05/2018] [Indexed: 01/30/2023] Open
Abstract
BACKGROUND For patients starting treatment for depression, current guidelines recommend titrating the antidepressant dosage to the maximum of the licenced range if tolerated. When patients do not achieve remission within several weeks, recommendations include adding or switching to another antidepressant. However, the relative merits of these guideline strategies remain unestablished. METHODS This multi-centre, open-label, assessor-blinded, pragmatic trial involved two steps. Step 1 used open-cluster randomisation, allocating clinics into those titrating sertraline up to 50 mg/day or 100 mg/day by week 3. Step 2 used central randomisation to allocate patients who did not remit after 3 weeks of treatment to continue sertraline, to add mirtazapine or to switch to mirtazapine. The primary outcome was depression severity measured with the Patient Health Questionnaire-9 (PHQ-9) (scores between 0 and 27; higher scores, greater depression) at week 9. We applied mixed-model repeated-measures analysis adjusted for key baseline covariates. RESULTS Between December 2010 and March 2015, we recruited 2011 participants with hitherto untreated major depression at 48 clinics in Japan. In step 1, 970 participants were allocated to the 50 mg/day and 1041 to the 100 mg/day arms; 1927 (95.8%) provided primary outcomes. There was no statistically significant difference in the adjusted PHQ-9 score at week 9 between the 50 mg/day arm and the 100 mg/day arm (0.25 point, 95% confidence interval (CI), - 0.58 to 1.07, P = 0.55). Other outcomes proved similar in the two groups. In step 2, 1646 participants not remitted by week 3 were randomised to continue sertraline (n = 551), to add mirtazapine (n = 537) or to switch to mirtazapine (n = 558): 1613 (98.0%) provided primary outcomes. At week 9, adding mirtazapine achieved a reduction in PHQ-9 scores of 0.99 point (0.43 to 1.55, P = 0.0012); switching achieved a reduction of 1.01 points (0.46 to 1.56, P = 0.0012), both relative to continuing sertraline. Combination increased the percentage of remission by 12.4% (6.1 to 19.0%) and switching by 8.4% (2.5 to 14.8%). There were no differences in adverse effects. CONCLUSIONS In patients with new onset depression, we found no advantage of titrating sertraline to 100 mg vs 50 mg. Patients unremitted by week 3 gained a small benefit in reduction of depressive symptoms at week 9 by switching sertraline to mirtazapine or by adding mirtazapine. TRIAL REGISTRATION ClinicalTrials.gov, NCT01109693 . Registered on 23 April 2010.
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Affiliation(s)
| | - Toshi A Furukawa
- Department of Health Promotion of Human Behavior, Kyoto University Graduate School of Medicine / School of Public Health, Yoshida Konoe-cho, Sakyo-ku, Kyoto, 606-8501, Japan.
| | | | | | | | | | | | | | | | | | | | | | - Masaki Kondo
- Department of Psychiatry and Cognitive-Behavioral Medicine, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan
| | - Yasumasa Okamoto
- Department of Neuropsychiatry, Hiroshima University Graduate School of Biomedical & Health Sciences, Hiroshima, Japan
| | - Hirokazu Fujita
- Center to Promote Creativity in Medical Education, Kochi Medical School, Kochi University, Nankoku, Japan
| | - Motomu Suga
- Department of Neuropsychiatry, University of Tokyo Hospital, Tokyo, Japan
| | - Shingo Yasumoto
- Department of Neuropsychiatry, Kurume University Medical School, Kurume, Japan
| | - Naohisa Tsujino
- Department of Psychiatry, Toho University School of Medicine, Tokyo, Japan
| | - Takeshi Inoue
- Department of Neuropsychiatry, Tokyo Medical University, Tokyo, Japan
| | - Noboru Fujise
- Department of Neuropsychiatry, Kumamoto University Graduate School of Medicine, Kumamoto, Japan
| | - Tatsuo Akechi
- Department of Psychiatry and Cognitive-Behavioral Medicine, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan
| | - Mitsuhiko Yamada
- Department of Neuropsychopharmacology, National Center of Neurology and Psychiatry, Tokyo, Japan
| | - Shinji Shimodera
- Center to Promote Creativity in Medical Education, Kochi Medical School, Kochi University, Nankoku, Japan
| | - Norio Watanabe
- Department of Health Promotion of Human Behavior, Kyoto University Graduate School of Medicine / School of Public Health, Yoshida Konoe-cho, Sakyo-ku, Kyoto, 606-8501, Japan
| | - Masatoshi Inagaki
- Department of Neuropsychiatry, Okayama University Hospital, Okayama, Japan
| | | | - Yusuke Ogawa
- Department of Health Promotion of Human Behavior, Kyoto University Graduate School of Medicine / School of Public Health, Yoshida Konoe-cho, Sakyo-ku, Kyoto, 606-8501, Japan
| | - Nozomi Takeshima
- Department of Health Promotion of Human Behavior, Kyoto University Graduate School of Medicine / School of Public Health, Yoshida Konoe-cho, Sakyo-ku, Kyoto, 606-8501, Japan
| | - Yu Hayasaka
- Department of Health Promotion of Human Behavior, Kyoto University Graduate School of Medicine / School of Public Health, Yoshida Konoe-cho, Sakyo-ku, Kyoto, 606-8501, Japan
| | - Aran Tajika
- Department of Health Promotion of Human Behavior, Kyoto University Graduate School of Medicine / School of Public Health, Yoshida Konoe-cho, Sakyo-ku, Kyoto, 606-8501, Japan
| | - Kiyomi Shinohara
- Department of Health Promotion of Human Behavior, Kyoto University Graduate School of Medicine / School of Public Health, Yoshida Konoe-cho, Sakyo-ku, Kyoto, 606-8501, Japan
| | - Naohiro Yonemoto
- Department of Biostatistics, Kyoto University Graduate School of Medicine / School of Public Health, Kyoto, Japan
| | - Shiro Tanaka
- Department of Clinical Biostatistics, Kyoto University Graduate School of Medicine / School of Public Health, Kyoto, Japan
| | - Qi Zhou
- Departments of Clinical Epidemiology and Biostatistics and of Medicine, McMaster University, Hamilton, Canada
| | - Gordon H Guyatt
- Departments of Clinical Epidemiology and Biostatistics and of Medicine, McMaster University, Hamilton, Canada
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Lenze EJ, Ramsey A, Brown PJ, Reynolds CF, Mulsant BH, Lavretsky H, Roose SP. Older Adults' Perspectives on Clinical Research: A Focus Group and Survey Study. Am J Geriatr Psychiatry 2016; 24:893-902. [PMID: 27591916 PMCID: PMC5026966 DOI: 10.1016/j.jagp.2016.07.022] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/28/2016] [Revised: 07/25/2016] [Accepted: 07/28/2016] [Indexed: 10/21/2022]
Abstract
OBJECTIVES Clinical trials can benefit from patient perspectives to inform trial design, such as choice of outcome measures. We engaged older adults in focus groups and surveys to get their perspective regarding needs in clinical research. The goal was to inform the development of a new clinical trial of medication strategies for treatment-resistant depression in older adults. METHODS Older adults with depression participated in focus groups and a subsequent survey in St. Louis and New York. They were queried regarding research design features including outcomes, clinical management, mobile technology and iPad-administered assessments, the collection of DNA, and the receipt of their personal results. RESULTS Patients told us: (1) psychological well-being and symptomatic remission are outcomes that matter to them; (2) it is important to measure not only benefits but risks (such as risk of falling) of medications; (3) for pragmatic trials in clinical settings, the research team should provide support to clinicians to ensure that medications are properly prescribed; (4) technology-based assessments are acceptable but there were concerns about data security and burden; (5) DNA testing is very important if it could improve precision care; (6) participants want to receive aggregate findings and their own personal results at the end of the study. CONCLUSIONS Patients gave useful and wide-ranging guidance regarding clinical and comparative effectiveness research in older adults. We discuss these findings with the goal of making the next generation of geriatric studies more impactful and patient-centered.
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Affiliation(s)
- Eric J. Lenze
- Washington University, St Louis, Missouri (Department of Psychiatry, 660 S. Euclid Box 8134, St Louis, MO 63110
| | - Alex Ramsey
- Washington University, St Louis, Missouri (Department of Psychiatry, 660 S. Euclid Box 8134, St Louis, MO 63110
| | - Patrick J. Brown
- College of Physicians and Surgeons, Columbia University and New York State Psychiatric Institute
| | | | - Benoit H. Mulsant
- Centre for Addiction and Mental Health and University of Toronto Department of Psychiatry
| | - Helen Lavretsky
- UCLA, UCLA Semel Institute for Neuroscience and Human Behavior
| | - Steven P. Roose
- College of Physicians and Surgeons, Columbia University and New York State Psychiatric Institute
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