Reference Citation Analysis: Find an Article, Find a Category, Find a Journal, Find a Scholar

For: Hedden SL, Woolson RF, Carter RE, Palesch Y, Upadhyaya HP, Malcolm RJ. The impact of loss to follow-up on hypothesis tests of the treatment effect for several statistical methods in substance abuse clinical trials. J Subst Abuse Treat 2009;37:54-63. [PMID: 19008067 PMCID: PMC2707817 DOI: 10.1016/j.jsat.2008.09.011] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2008] [Revised: 09/23/2008] [Accepted: 09/24/2008] [Indexed: 12/17/2022]

For:	Hedden SL, Woolson RF, Carter RE, Palesch Y, Upadhyaya HP, Malcolm RJ. The impact of loss to follow-up on hypothesis tests of the treatment effect for several statistical methods in substance abuse clinical trials. J Subst Abuse Treat 2009;37:54-63. [PMID: 19008067 PMCID: PMC2707817 DOI: 10.1016/j.jsat.2008.09.011] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2008] [Revised: 09/23/2008] [Accepted: 09/24/2008] [Indexed: 12/17/2022]

Number

Cited by Other Article(s)

Azadmanjir Z, Khormali M, Sadeghi-Naini M, Baigi V, Pirnejad H, Dashtkoohi M, Ghodsi Z, Jazayeri SB, Shakeri A, Mohammadzadeh M, Bagheri L, Lotfi MS, Daliri S, Azarhomayoun A, Sadeghi-Bazargani H, O'reilly G, Rahimi-Movaghar V. Post-discharge follow-up of patients with spine trauma in the National Spinal Cord Injury Registry of Iran during the COVID-19 pandemic: Challenges and lessons learned. Chin J Traumatol 2024;27:173-179. [PMID: 38016878 PMCID: PMC11138348 DOI: 10.1016/j.cjtee.2023.10.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/14/2022] [Revised: 09/10/2023] [Accepted: 10/23/2023] [Indexed: 11/30/2023] Open

Abstract

PURPOSE

The purpose of the National Spinal Cord Injury Registry of Iran (NSCIR-IR) is to create an infrastructure to assess the quality of care for spine trauma and in this study, we aim to investigate whether the NSCIR-IR successfully provides necessary post-discharge follow-up data for these patients.

METHODS

An observational prospective study was conducted from April 11, 2021 to April 22, 2022 in 8 centers enrolled in NSCIR-IR, respectively Arak, Rasht, Urmia, Shahroud, Yazd, Kashan, Tabriz, and Tehran. Patients were classified into 3 groups based on their need for care resources, respectively: (1) non-spinal cord injury (SCI) patients without surgery (group 1), (2) non-SCI patients with surgery (group 2), and (3) SCI patients (group 3). The assessment tool was a self-designed questionnaire to evaluate the care quality in 3 phases: pre-hospital, in-hospital, and post-hospital. The data from the first 2 phases were collected through the registry. The post-hospital data were collected by conducting follow-up assessments. Telephone follow-ups were conducted for groups 1 and 2 (non-SCI patients), while group 3 (SCI patients) had a face-to-face visit. This study took place during the COVID-19 pandemic. Data on age and time interval from injury to follow-up were expressed as mean ± standard deviation (SD) and response rate and follow-up loss as a percentage.

RESULTS

Altogether 1538 telephone follow-up records related to 1292 patients were registered in the NSCIR-IR. Of the total calls, 918 (71.05%) were related to successful follow-ups, but 38 cases died and thus were excluded from data analysis. In the end, post-hospital data from 880 patients alive were gathered. The success rate of follow-ups by telephone for groups 1 and 2 was 73.38% and 67.05% respectively, compared to 66.67% by face-to-face visits for group 3, which was very hard during the COVID-19 pandemic. The data completion rate after discharge ranged from 48% - 100%, 22% - 100% and 29% - 100% for groups 1 - 3.

CONCLUSIONS

To improve patient accessibility, NSCIR-IR should take measures during data gathering to increase the accuracy of registered contact information. Regarding the loss to follow-ups of SCI patients, NSCIR-IR should find strategies for remote assessment or motivate them to participate in follow-ups through, for example, providing transportation facilities or financial support.

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Affiliation(s)

Zahra Azadmanjir Health Information Management Department, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran; Sina Trauma and Surgery Research Center, Tehran University of Medical Sciences, Tehran, Iran
Moein Khormali Sina Trauma and Surgery Research Center, Tehran University of Medical Sciences, Tehran, Iran
Mohsen Sadeghi-Naini Department of Neurosurgery, Lorestan University of Medical Sciences, Khoram-Abad, Iran
Vali Baigi Sina Trauma and Surgery Research Center, Tehran University of Medical Sciences, Tehran, Iran; Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
Habibollah Pirnejad Patient Safety Research Center, Clinical Research Institute, Urmia University of Medical Sciences, Urmia, Iran; Erasmus School of Health Policy & Management (ESHPM), Erasmus University Rotterdam, Rotterdam, the Netherlands
Mohammad Dashtkoohi Sina Trauma and Surgery Research Center, Tehran University of Medical Sciences, Tehran, Iran; Brain and Spinal Cord Injury Research Center, Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Iran; Students Scientific Research Center (SSRC), Tehran University of Medical Sciences, Tehran, Iran
Zahra Ghodsi Sina Trauma and Surgery Research Center, Tehran University of Medical Sciences, Tehran, Iran; Brain and Spinal Cord Injury Research Center, Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Iran
Seyed Behnam Jazayeri Sina Trauma and Surgery Research Center, Tehran University of Medical Sciences, Tehran, Iran
Aidin Shakeri Department of Neurosurgery, Arak University of Medical Sciences, Arak, Iran
Mahdi Mohammadzadeh Trauma Research Center, Kashan University of Medical Sciences, Kashan, Iran
Laleh Bagheri Shahid Rahnemoun Hospital, Shahid Sadoughi University of Medical Sciences, Yazd, Iran
Mohammad-Sajjad Lotfi Trauma Nursing Research Centre, Faculty of Nursing and Midwifery, Kashan University of Medical Sciences, Kashan, Iran
Salman Daliri Clinical Research Development Unit, Imam Hossein Hospital, Shahroud University of Medical Sciences, Shahroud, Iran
Amir Azarhomayoun Sina Trauma and Surgery Research Center, Tehran University of Medical Sciences, Tehran, Iran
Homayoun Sadeghi-Bazargani Research Center for Evidence Based Medicine, Faculty of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran; Road Traffic Injury Research Center, Tabriz University of Medical Sciences, Tabriz, Iran
Gerard O'reilly School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia; National Trauma Research Institute, The Alfred, Melbourne, Australia
Vafa Rahimi-Movaghar Sina Trauma and Surgery Research Center, Tehran University of Medical Sciences, Tehran, Iran; Brain and Spinal Cord Injury Research Center, Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Iran; Department of Neurosurgery, Shariati Hospital, Tehran University of Medical Sciences, Tehran, Iran; Universal Scientific Education and Research Network (USERN), Tehran, Iran; Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran.

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Kaplan A, Nelson D. Simple Bayesian models for missing binary outcomes in randomized controlled trials. Stat Med 2023;42:4377-4391. [PMID: 37573785 DOI: 10.1002/sim.9866] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Revised: 07/20/2023] [Accepted: 07/24/2023] [Indexed: 08/15/2023]

Thongprayoon C, Miao J, Jadlowiec CC, Mao SA, Mao MA, Leeaphorn N, Kaewput W, Pattharanitima P, Tangpanithandee S, Krisanapan P, Nissaisorakarn P, Cooper M, Cheungpasitporn W. Differences between Kidney Transplant Recipients from Deceased Donors with Diabetes Mellitus as Identified by Machine Learning Consensus Clustering. J Pers Med 2023;13:1094. [PMID: 37511707 PMCID: PMC10381319 DOI: 10.3390/jpm13071094] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2023] [Revised: 06/21/2023] [Accepted: 07/01/2023] [Indexed: 07/30/2023] Open

Abstract

Clinical outcomes of deceased donor kidney transplants coming from diabetic donors currently remain inconsistent, possibly due to high heterogeneities in this population. Our study aimed to cluster recipients of diabetic deceased donor kidney transplants using an unsupervised machine learning approach in order to identify subgroups with high risk of inferior outcomes and potential variables associated with these outcomes. Consensus cluster analysis was performed based on recipient-, donor-, and transplant-related characteristics in 7876 recipients of diabetic deceased donor kidney transplants from 2010 to 2019 in the OPTN/UNOS database. We determined the important characteristics of each assigned cluster and compared the post-transplant outcomes between the clusters. Consensus cluster analysis identified three clinically distinct clusters. Recipients in cluster 1 (n = 2903) were characterized by oldest age (64 ± 8 years), highest rate of comorbid diabetes mellitus (55%). They were more likely to receive kidney allografts from donors that were older (58 ± 6.3 years), had hypertension (89%), met expanded criteria donor (ECD) status (78%), had a high rate of cerebrovascular death (63%), and carried a high kidney donor profile index (KDPI). Recipients in cluster 2 (n = 687) were younger (49 ± 13 years) and all were re-transplant patients with higher panel reactive antibodies (PRA) (88 [IQR 46, 98]) who received kidneys from younger (44 ± 11 years), non-ECD deceased donors (88%) with low numbers of HLA mismatch (4 [IQR 2, 5]). The cluster 3 cohort was characterized by first-time kidney transplant recipients (100%) who received kidney allografts from younger (42 ± 11 years), non-ECD deceased donors (98%). Compared to cluster 3, cluster 1 had higher incidence of primary non-function, delayed graft function, patient death and death-censored graft failure, whereas cluster 2 had higher incidence of delayed graft function and death-censored graft failure but comparable primary non-function and patient death. An unsupervised machine learning approach characterized diabetic donor kidney transplant patients into three clinically distinct clusters with differing outcomes. Our data highlight opportunities to improve utilization of high KDPI kidneys coming from diabetic donors in recipients with survival-limiting comorbidities such as those observed in cluster 1.

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Affiliation(s)

Charat Thongprayoon Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Rochester, MN 55905, USA; (C.T.); (J.M.); (S.T.); (P.K.)
Jing Miao Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Rochester, MN 55905, USA; (C.T.); (J.M.); (S.T.); (P.K.)
Caroline C. Jadlowiec Division of Transplant Surgery, Mayo Clinic, Phoenix, AZ 85054, USA;
Shennen A. Mao Division of Transplant Surgery, Mayo Clinic, Jacksonville, FL 32224, USA;
Michael A. Mao Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Jacksonville, FL 32224, USA; (M.A.M.); (N.L.)
Napat Leeaphorn Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Jacksonville, FL 32224, USA; (M.A.M.); (N.L.)
Wisit Kaewput Department of Military and Community Medicine, Phramongkutklao College of Medicine, Bangkok 10400, Thailand;
Pattharawin Pattharanitima Department of Internal Medicine, Faculty of Medicine, Thammasat University, Pathum Thani 12120, Thailand;
Supawit Tangpanithandee Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Rochester, MN 55905, USA; (C.T.); (J.M.); (S.T.); (P.K.)
Pajaree Krisanapan Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Rochester, MN 55905, USA; (C.T.); (J.M.); (S.T.); (P.K.) Department of Internal Medicine, Faculty of Medicine, Thammasat University, Pathum Thani 12120, Thailand;
Pitchaphon Nissaisorakarn Department of Medicine, Division of Nephrology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA;
Matthew Cooper Medical College of Wisconsin, Milwaukee, WI 53226, USA;
Wisit Cheungpasitporn Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Rochester, MN 55905, USA; (C.T.); (J.M.); (S.T.); (P.K.)

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Thongprayoon C, Vaitla P, Jadlowiec CC, Leeaphorn N, Mao SA, Mao MA, Qureshi F, Kaewput W, Qureshi F, Tangpanithandee S, Krisanapan P, Pattharanitima P, Acharya PC, Nissaisorakarn P, Cooper M, Cheungpasitporn W. Distinct Phenotypes of Non-Citizen Kidney Transplant Recipients in the United States by Machine Learning Consensus Clustering. MEDICINES (BASEL, SWITZERLAND) 2023;10:25. [PMID: 37103780 PMCID: PMC10144541 DOI: 10.3390/medicines10040025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/03/2022] [Accepted: 03/24/2023] [Indexed: 04/28/2023]

Abstract

Better understanding of the different phenotypes/subgroups of non-U.S. citizen kidney transplant recipients may help the transplant community to identify strategies that improve outcomes among non-U.S. citizen kidney transplant recipients. This study aimed to cluster non-U.S. citizen kidney transplant recipients using an unsupervised machine learning approach; Methods: We conducted a consensus cluster analysis based on recipient-, donor-, and transplant- related characteristics in non-U.S. citizen kidney transplant recipients in the United States from 2010 to 2019 in the OPTN/UNOS database using recipient, donor, and transplant-related characteristics. Each cluster's key characteristics were identified using the standardized mean difference. Post-transplant outcomes were compared among the clusters; Results: Consensus cluster analysis was performed in 11,300 non-U.S. citizen kidney transplant recipients and identified two distinct clusters best representing clinical characteristics. Cluster 1 patients were notable for young age, preemptive kidney transplant or dialysis duration of less than 1 year, working income, private insurance, non-hypertensive donors, and Hispanic living donors with a low number of HLA mismatch. In contrast, cluster 2 patients were characterized by non-ECD deceased donors with KDPI <85%. Consequently, cluster 1 patients had reduced cold ischemia time, lower proportion of machine-perfused kidneys, and lower incidence of delayed graft function after kidney transplant. Cluster 2 had higher 5-year death-censored graft failure (5.2% vs. 9.8%; p < 0.001), patient death (3.4% vs. 11.4%; p < 0.001), but similar one-year acute rejection (4.7% vs. 4.9%; p = 0.63), compared to cluster 1; Conclusions: Machine learning clustering approach successfully identified two clusters among non-U.S. citizen kidney transplant recipients with distinct phenotypes that were associated with different outcomes, including allograft loss and patient survival. These findings underscore the need for individualized care for non-U.S. citizen kidney transplant recipients.

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Affiliation(s)

Charat Thongprayoon Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Rochester, MN 55905, USA (S.T.); (P.K.)
Pradeep Vaitla Division of Nephrology, University of Mississippi Medical Center, Jackson, MS 39216, USA
Caroline C. Jadlowiec Division of Transplant Surgery, Mayo Clinic, Phoenix, AZ 85054, USA
Napat Leeaphorn Renal Transplant Program, University of Missouri-Kansas City School of Medicine/Saint Luke’s Health System, Kansas City, MO 64108, USA
Shennen A. Mao Division of Transplant Surgery, Mayo Clinic, Jacksonville, FL 32224, USA
Michael A. Mao Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Jacksonville, FL 32224, USA
Fahad Qureshi School of Medicine, University of Missouri-Kansas City, Kansas City, MO 64108, USA
Wisit Kaewput Department of Military and Community Medicine, Phramongkutklao College of Medicine, Bangkok 10400, Thailand
Fawad Qureshi Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Rochester, MN 55905, USA (S.T.); (P.K.)
Supawit Tangpanithandee Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Rochester, MN 55905, USA (S.T.); (P.K.)
Pajaree Krisanapan Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Rochester, MN 55905, USA (S.T.); (P.K.) Department of Military and Community Medicine, Phramongkutklao College of Medicine, Bangkok 10400, Thailand
Pattharawin Pattharanitima Division of Nephrology, Department of Internal Medicine, Faculty of Medicine Thammasat University, Pathum Thani 12120, Thailand
Prakrati C. Acharya Division of Nephrology, Texas Tech Health Sciences Center El Paso, El Paso, TX 79905, USA
Pitchaphon Nissaisorakarn Department of Medicine, Division of Nephrology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
Matthew Cooper Medstar Georgetown Transplant Institute, Georgetown University School of Medicine, Washington, DC 21042, USA
Wisit Cheungpasitporn Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Rochester, MN 55905, USA (S.T.); (P.K.)

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Tangpanithandee S, Thongprayoon C, Jadlowiec CC, Mao SA, Mao MA, Vaitla P, Leeaphorn N, Kaewput W, Pattharanitima P, Krisanapan P, Nissaisorakarn P, Cooper M, Cheungpasitporn W. Clinical Phenotypes of Dual Kidney Transplant Recipients in the United States as Identified through Machine Learning Consensus Clustering. MEDICINA (KAUNAS, LITHUANIA) 2022;58:1831. [PMID: 36557033 PMCID: PMC9783488 DOI: 10.3390/medicina58121831] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Revised: 12/03/2022] [Accepted: 12/09/2022] [Indexed: 12/14/2022]

Abstract

Background and Objectives: Our study aimed to cluster dual kidney transplant recipients using an unsupervised machine learning approach to characterize donors and recipients better and to compare the survival outcomes across these various clusters. Materials and Methods: We performed consensus cluster analysis based on recipient-, donor-, and transplant-related characteristics in 2821 dual kidney transplant recipients from 2010 to 2019 in the OPTN/UNOS database. We determined the important characteristics of each assigned cluster and compared the post-transplant outcomes between clusters. Results: Two clinically distinct clusters were identified by consensus cluster analysis. Cluster 1 patients was characterized by younger patients (mean recipient age 49 ± 13 years) who received dual kidney transplant from pediatric (mean donor age 3 ± 8 years) non-expanded criteria deceased donor (100% non-ECD). In contrast, Cluster 2 patients were characterized by older patients (mean recipient age 63 ± 9 years) who received dual kidney transplant from adult (mean donor age 59 ± 11 years) donor with high kidney donor profile index (KDPI) score (59% had KDPI ≥ 85). Cluster 1 had higher patient survival (98.0% vs. 94.6% at 1 year, and 92.1% vs. 76.3% at 5 years), and lower acute rejection (4.2% vs. 6.1% within 1 year), when compared to cluster 2. Death-censored graft survival was comparable between two groups (93.5% vs. 94.9% at 1 year, and 89.2% vs. 84.8% at 5 years). Conclusions: In summary, DKT in the United States remains uncommon. Two clusters, based on specific recipient and donor characteristics, were identified through an unsupervised machine learning approach. Despite varying differences in donor and recipient age between the two clusters, death-censored graft survival was excellent and comparable. Broader utilization of DKT from high KDPI kidneys and pediatric en bloc kidneys should be encouraged to better address the ongoing organ shortage.

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Thongprayoon C, Radhakrishnan Y, Jadlowiec CC, Mao SA, Mao MA, Vaitla P, Acharya PC, Leeaphorn N, Kaewput W, Pattharanitima P, Tangpanithandee S, Krisanapan P, Nissaisorakarn P, Cooper M, Cheungpasitporn W. Characteristics of Kidney Recipients of High Kidney Donor Profile Index Kidneys as Identified by Machine Learning Consensus Clustering. J Pers Med 2022;12:1992. [PMID: 36556213 PMCID: PMC9782675 DOI: 10.3390/jpm12121992] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2022] [Revised: 11/24/2022] [Accepted: 11/29/2022] [Indexed: 12/04/2022] Open

Abstract

Background: Our study aimed to characterize kidney transplant recipients who received high kidney donor profile index (KDPI) kidneys using unsupervised machine learning approach. Methods: We used the OPTN/UNOS database from 2010 to 2019 to perform consensus cluster analysis based on recipient-, donor-, and transplant-related characteristics in 8935 kidney transplant recipients from deceased donors with KDPI ≥ 85%. We identified each cluster’s key characteristics using the standardized mean difference of >0.3. We compared the posttransplant outcomes among the assigned clusters. Results: Consensus cluster analysis identified 6 clinically distinct clusters of kidney transplant recipients from donors with high KDPI. Cluster 1 was characterized by young, black, hypertensive, non-diabetic patients who were on dialysis for more than 3 years before receiving kidney transplant from black donors; cluster 2 by elderly, white, non-diabetic patients who had preemptive kidney transplant or were on dialysis less than 3 years before receiving kidney transplant from older white donors; cluster 3 by young, non-diabetic, retransplant patients; cluster 4 by young, non-obese, non-diabetic patients who received dual kidney transplant from pediatric, black, non-hypertensive non-ECD deceased donors; cluster 5 by low number of HLA mismatch; cluster 6 by diabetes mellitus. Cluster 4 had the best patient survival, whereas cluster 3 had the worst patient survival. Cluster 2 had the best death-censored graft survival, whereas cluster 4 and cluster 3 had the worst death-censored graft survival at 1 and 5 years, respectively. Cluster 2 and cluster 4 had the best overall graft survival at 1 and 5 years, respectively, whereas cluster 3 had the worst overall graft survival. Conclusions: Unsupervised machine learning approach kidney transplant recipients from donors with high KDPI based on their pattern of clinical characteristics into 6 clinically distinct clusters.

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Affiliation(s)

Charat Thongprayoon Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Rochester, MN 55905, USA
Yeshwanter Radhakrishnan Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Rochester, MN 55905, USA
Caroline C. Jadlowiec Division of Transplant Surgery, Mayo Clinic, Phoenix, AZ 85054, USA
Shennen A. Mao Division of Transplant Surgery, Mayo Clinic, Jacksonville, FL 32224, USA
Michael A. Mao Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Jacksonville, FL 32224, USA
Pradeep Vaitla Division of Nephrology, University of Mississippi Medical Center, Jackson, MS 39216, USA
Prakrati C. Acharya Division of Nephrology, Texas Tech Health Sciences Center El Paso, El Paso, TX 79905, USA
Napat Leeaphorn Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Jacksonville, FL 32224, USA
Wisit Kaewput Department of Military and Community Medicine, Phramongkutklao College of Medicine, Bangkok 10400, Thailand
Pattharawin Pattharanitima Department of Internal Medicine, Faculty of Medicine, Thammasat University, Pathum Thani 12120, Thailand
Supawit Tangpanithandee Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Rochester, MN 55905, USA Chakri Naruebodindra Medical Institute, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Samut Prakan 10540, Thailand
Pajaree Krisanapan Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Rochester, MN 55905, USA Department of Internal Medicine, Faculty of Medicine, Thammasat University, Pathum Thani 12120, Thailand
Pitchaphon Nissaisorakarn Department of Medicine, Division of Nephrology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
Matthew Cooper Medstar Georgetown Transplant Institute, Georgetown University School of Medicine, Washington, DC 21042, USA
Wisit Cheungpasitporn Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Rochester, MN 55905, USA

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Makowski M, Bhagat R, Chevalier S, Gilbert SA, Görtz DR, Kozińska M, Nadolny P, Suprin M, Turri S. Historical Benchmarks for Quality Tolerance Limits Parameters in Clinical Trials. Ther Innov Regul Sci 2021;55:1265-1273. [PMID: 34453269 PMCID: PMC8492573 DOI: 10.1007/s43441-021-00335-3] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2021] [Accepted: 08/13/2021] [Indexed: 11/04/2022]

Gwinnutt JM, Hyrich KL, Lunt M, Barton A, Verstappen SMM. Long-term outcomes of patients who rate symptoms of rheumatoid arthritis as 'satisfactory'. Rheumatology (Oxford) 2021;59:1853-1861. [PMID: 31729526 PMCID: PMC7382599 DOI: 10.1093/rheumatology/kez497] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2019] [Revised: 08/26/2019] [Indexed: 11/14/2022] Open

Dermody SS, Tessier KM, Meier E, al'Absi M, Denlinger-Apte RL, Drobes DJ, Jensen J, Koopmeiners JS, Pacek LR, Tidey JW, Vandrey R, Donny E, Hatsukami D. An Evaluation of Potential Unintended Consequences of a Nicotine Product Standard: A Focus on Drinking History and Outcomes. Nicotine Tob Res 2020;23:1168-1175. [PMID: 33220047 DOI: 10.1093/ntr/ntaa236] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2020] [Accepted: 11/16/2020] [Indexed: 01/02/2023]

Abstract

INTRODUCTION

A nicotine product standard reducing the nicotine content in cigarettes could improve public health by reducing smoking. This study evaluated the potential unintended consequences of a reduced nicotine product standard by examining its effects on (1) smoking behaviors based on drinking history; (2) drinking behavior; and (3) daily associations between smoking and drinking.

METHODS

Adults who smoke daily (n = 752) in the United States were randomly assigned to smoke very low nicotine content (VLNC) cigarettes versus normal nicotine content (NNC; control) cigarettes for 20 weeks. Linear mixed models determined if baseline drinking moderated the effects of VLNC versus NNC cigarettes on Week 20 smoking outcomes. Time-varying effect models estimated the daily association between smoking VLNC cigarettes and drinking outcomes.

RESULTS

Higher baseline alcohol use (vs no use or lower use) was associated with a smaller effect of VLNC on Week 20 urinary total nicotine equivalents (ps < .05). No additional moderation was supported (ps > .05). In the subsample who drank (n = 415), in the VLNC versus NNC condition, daily alcohol use was significantly reduced from Weeks 17 to 20 and odds of binge drinking were significantly reduced from Weeks 9 to 17. By Week 7, in the VLNC cigarette condition (n = 272), smoking no longer predicted alcohol use but remained associated with binge drinking.

CONCLUSIONS

We did not support negative unintended consequences of a nicotine product standard. Nicotine reduction in cigarettes generally affected smoking behavior for individuals who do not drink or drink light-to-moderate amounts in similar ways. Extended VLNC cigarette use may improve public health by reducing drinking behavior.

IMPLICATIONS

There was no evidence that a VLNC product standard would result in unintended consequences based on drinking history or when considering alcohol outcomes. Specifically, we found that a very low nicotine standard in cigarettes generally reduces smoking outcomes for those who do not drink and those who drink light-to-moderate amounts. Furthermore, an added public health benefit of a very low nicotine standard for cigarettes could be a reduction in alcohol use and binge drinking over time. Finally, smoking VLNC cigarettes may result in a decoupling of the daily associations between smoking and drinking.

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Jannat-Khah DP, Unterbrink M, McNairy M, Pierre S, Fitzgerald DW, Pape J, Evans A. Treating loss-to-follow-up as a missing data problem: a case study using a longitudinal cohort of HIV-infected patients in Haiti. BMC Public Health 2018;18:1269. [PMID: 30453995 PMCID: PMC6245624 DOI: 10.1186/s12889-018-6115-0] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2018] [Accepted: 10/12/2018] [Indexed: 11/30/2022] Open

Abstract

Background

HIV programs are often assessed by the proportion of patients who are alive and retained in care; however some patients are categorized as lost to follow-up (LTF) and have unknown vital status. LTF is not an outcome but a mixed category of patients who have undocumented death, transfer and disengagement from care. Estimating vital status (dead versus alive) among this category is critical for survival analyses and program evaluation.

Methods

We used three methods to estimate survival in the cohort and to ascertain factors associated with death among the first cohort of HIV positive patients to receive antiretroviral therapy in Haiti: complete case (CC) (drops missing), Inverse Probability Weights (IPW) (uses tracking data) and Multiple Imputation with Chained Equations (MICE) (imputes missing data). Logistic regression was used to calculate odds ratios and 95% confidence intervals for adjusted models for death at 10 years. The logistic regression models controlled for sex, age, severe poverty (living on <$1 USD per day), Port-au-Prince residence and baseline clinical characteristics of weight, CD4, WHO stage and tuberculosis diagnosis.

Results

Age, severe poverty, baseline weight and WHO stage were statistically significant predictors of AIDS related mortality across all models. Gender was only statistically significant in the MICE model but had at least a 10% difference in odds ratios across all models.

Conclusion

Each of these methods had different assumptions and differed in the number of observations included due to how missing values were addressed. We found MICE to be most robust in predicting survival status as it allowed us to impute missing data so that we had the maximum number of observations to perform regression analyses. MICE also provides a complementary alternative for estimating survival among patients with unassigned vital status. Additionally, the results were easier to interpret, less likely to be biased and provided an alternative to a problem that is often commented upon in the extant literature.

Electronic supplementary material

The online version of this article (10.1186/s12889-018-6115-0) contains supplementary material, which is available to authorized users.

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Kim H, Cutter GR, George B, Chen Y. Understanding and Preventing Loss to Follow-up: Experiences From the Spinal Cord Injury Model Systems. Top Spinal Cord Inj Rehabil 2018;24:97-109. [PMID: 29706754 DOI: 10.1310/sci2402-97] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]

Ciulla TA, Huang F, Westby K, Williams DF, Zaveri S, Patel SC. Real-world Outcomes of Anti-Vascular Endothelial Growth Factor Therapy in Neovascular Age-Related Macular Degeneration in the United States. Ophthalmol Retina 2018;2:645-653. [PMID: 31047372 DOI: 10.1016/j.oret.2018.01.006] [Citation(s) in RCA: 79] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2017] [Revised: 11/29/2017] [Accepted: 01/11/2018] [Indexed: 12/17/2022]

Abstract

PURPOSE

Real-world visual outcomes of anti-vascular endothelial growth factor (anti-VEGF) therapy for neovascular age-related macular degeneration (nAMD) have been reported in cohorts outside of the United States. This study sought to assess the relationship between presenting visual acuity (VA) and visual outcomes, as well as the potential impact of loss to follow-up, in real-world anti-VEGF-treated nAMD patients from the United States.

DESIGN

Retrospective study of aggregated, longitudinal electronic medical records obtained from a geographically diverse sample of US retina specialists and included in the Vestrum Health Retina Database.

PARTICIPANTS

Inclusion criteria were a diagnosis of nAMD, no previous treatment, and ≥3 monthly anti-VEGF injections in the first 4 months from diagnosis in patients diagnosed between January 2011 and July 2013.

METHODS

To model loss to follow-up, mutually exclusive cohorts of nAMD patients with loss to follow-up after specific time points of 6 and 12 months (i.e., no follow-up beyond) were compared with a separate cohort of patients who completed 24 months of follow-up ending prior to July 2015 (n = 2213).

MAIN OUTCOME MEASURE

VA outcomes were assessed on each cohort as a whole, with additional stratification by baseline VA.

RESULTS

The 6-, 12-, and 24-month cohorts received means of 5.4, 7.3, and 12.1 injections and showed no change, no change, and a mean change of +3.1 letters from baseline (95% confidence interval 1.8-4.4 letters, P < 0.01), respectively. When stratified by baseline VA, nearly all groups lose VA at their respective follow-up periods, except for those with baseline VA of 20/200 or worse.

CONCLUSIONS

Real-world nAMD patients in the United States receive fewer anti-VEGF injections and experience worse visual outcomes compared with patients in randomized clinical trials, consistent with non-US studies. Patients with better VA at presentation tend to be particularly vulnerable to vision loss. Compared with other patients, those ultimately lost to follow-up have worse visual outcomes at, or prior to, their final visit, suggesting that loss to follow-up may lead to overestimation of visual outcomes in clinical studies of nAMD.

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Olsen RE, Kroken RA, Bjørhovde S, Aanesen K, Jørgensen HA, Løberg EM, Johnsen E. Influence of different second generation antipsychotics on the QTc interval: A pragmatic study. World J Psychiatry 2016;6:442-448. [PMID: 28078208 PMCID: PMC5183996 DOI: 10.5498/wjp.v6.i4.442] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/30/2016] [Revised: 09/01/2016] [Accepted: 10/09/2016] [Indexed: 02/05/2023] Open

Abstract

AIM

To investigate whether differential influence on the QTc interval exists among four second generation antipsychotics (SGAs) in psychosis.

METHODS

Data were drawn from a pragmatic, randomized head-to-head trial of the SGAs risperidone, olanzapine, quetiapine, and ziprasidone in acute admissions patients with psychosis, and with follow-up visits at discharge or maximally 6-9 wk, 3, 6, 12 and 24 mo. Electrocardiograms were recorded on all visits. To mimic clinical shared decision-making, the patients were randomized not to a single drug, but to a sequence of the SGAs under investigation. The first drug in the sequence defined the randomization group, but the patient and/or clinician could choose an SGA later in the sequence if prior negative experiences with the first one(s) in the sequence had occurred. The study focuses on the time of, and actual use of the SGAs under investigation, that is until treatment discontinuation or change, in order to capture the direct medication effects on the QTc interval. Secondary intention-to-treat (ITT) analyses were also performed.

RESULTS

A total of 173 patients, with even distribution among the treatment groups, underwent ECG assessments. About 70% were males and 43% had never used antipsychotic drugs before the study. The mean antipsychotic doses in milligrams per day with standard deviations (SD) were 3.4 (1.2) for risperidone, 13.9 (4.6) for olanzapine, 325.9 (185.8) for quetiapine, and 97.2 (42.8) for ziprasidone treated groups. The time until discontinuation of the antipsychotic drug used did not differ in a statistically significant way among the groups (Log-Rank test: P = 0.171). The maximum QTc interval recorded during follow-up was 462 ms. Based on linear mixed effects analyses, the QTc interval change per day with standard error was -0.0030 (0.0280) for risperidone; -0.0099 (0.0108) for olanzapine; -0.0027 (0.0170) for quetiapine, and -0.0081 (0.0229) for ziprasidone. There were no statistically significant differences among the groups in this regard. LME analyses based on ITT groups (the randomization groups), revealed almost identical slopes with -0.0063 (0.0160) for risperidone, -0.0130 (0.0126) for olanzapine, -0.0034 (0.0168) for quetiapine, and -0.0045 (0.0225) for ziprasidone.

CONCLUSION

None of the SGAs under investigation led to statistically significant QTc prolongation. No statistically significant differences among the SGAs were found.

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Flecha OD, Douglas de Oliveira DW, Marques LS, Gonçalves PF. A commentary on randomized clinical trials: How to produce them with a good level of evidence. Perspect Clin Res 2016;7:75-80. [PMID: 27141473 PMCID: PMC4840795 DOI: 10.4103/2229-3485.179432] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open

Hallgren KA, McCrady BS. We-Language and Sustained Reductions in Drinking in Couple-Based Treatment for Alcohol Use Disorders. FAMILY PROCESS 2016;55:62-78. [PMID: 25809790 PMCID: PMC4577304 DOI: 10.1111/famp.12150] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/19/2023]

Abstract

Couple-based treatments for alcohol use disorders (AUDs) produce higher rates of abstinence than individual-based treatments and posit that active involvement of both identified patients (IPs) and significant others (SOs) is partly responsible for these improvements. Separate research on couples' communication has suggested that pronoun usage can indicate a communal approach to coping with health-related problems. The present study tested whether communal coping, indicated by use of more first-person plural pronouns ("we" language), fewer second-person pronouns ("you" language), and fewer first-person singular pronouns ("I" language), predicted improvements in abstinence in couple-based AUD treatment. Pronoun use was measured in first- and mid-treatment sessions for 188 heterosexual couples in four clinical trials of alcohol behavioral couple therapy (ABCT). Percentages of days abstinent were assessed during treatment and over a 6-month follow-up period. Greater IP and SO "we" language during both sessions was correlated with greater improvement in abstinent days during treatment. Greater SO "we" language during first- and mid-treatment sessions was correlated with greater improvement in abstinence at follow-up. Greater use of IP and SO "you" and "I" language had mixed correlations with abstinence, typically being unrelated to or predicting less improvement in abstinence. When all pronoun variables were entered into regression models, only greater IP "we" langue and lower IP "you" language predicted improvements in abstinence during treatment, and only SO "we" language predicted improvements during follow-up. Most pronoun categories had little or no association with baseline relationship distress. Results suggest that communal coping predicts better abstinence outcomes in couple-based AUD treatment.

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Rolland B, Labreuche J, Duhamel A, Deheul S, Gautier S, Auffret M, Pignon B, Valin T, Bordet R, Cottencin O. Baclofen for alcohol dependence: Relationships between baclofen and alcohol dosing and the occurrence of major sedation. Eur Neuropsychopharmacol 2015;25:1631-6. [PMID: 26095229 DOI: 10.1016/j.euroneuro.2015.05.008] [Citation(s) in RCA: 42] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/24/2015] [Revised: 04/29/2015] [Accepted: 05/25/2015] [Indexed: 11/29/2022]

Witkiewitz K, Falk DE, Kranzler HR, Litten RZ, Hallgren KA, O'Malley SS, Anton RF. Methods to analyze treatment effects in the presence of missing data for a continuous heavy drinking outcome measure when participants drop out from treatment in alcohol clinical trials. Alcohol Clin Exp Res 2015;38:2826-34. [PMID: 25421518 DOI: 10.1111/acer.12543] [Citation(s) in RCA: 51] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2014] [Accepted: 08/13/2014] [Indexed: 11/29/2022]

Abstract

BACKGROUND

Attrition is common in alcohol clinical trials and the resultant loss of data represents an important methodological problem. In the absence of a simulation study, the drinking outcomes among those who are lost to follow-up are not known. Individuals who drop out of treatment and continue to provide drinking data, however, may be a reasonable proxy group for making inferences about the drinking outcomes of those lost to follow-up.

METHODS

We used data from the COMBINE study, a multisite, randomized clinical trial, to examine drinking during the 4 months of treatment among individuals who dropped out of treatment but continued to provide drinking data (i.e., "treatment dropouts;" n = 185). First, we estimated the observed treatment effect size for naltrexone versus placebo in a sample that included both treatment completers (n = 961) and treatment dropouts (n = 185; total N = 1,146), as well as the observed treatment effect size among just those who dropped out of treatment (n = 185). In both the total sample (N = 1,146) and the dropout sample (n = 185), we then deleted the drinking data after treatment dropout from those 185 individuals to simulate missing data. Using the deleted data sets, we then estimated the effect of naltrexone on the continuous outcome percent heavy drinking days using 6 methods to handle missing data (last observation carried forward, baseline observation carried forward, placebo mean imputation, missing = heavy drinking days, multiple imputation (MI), and full information maximum likelihood [FIML]).

RESULTS

MI and FIML produced effect size estimates that were most similar to the true effects observed in the full data set in all analyses, while missing = heavy drinking days performed the worst.

CONCLUSIONS

Although missing drinking data should be avoided whenever possible, MI and FIML yield the best estimates of the treatment effect for a continuous outcome measure of heavy drinking when there is dropout in an alcohol clinical trial.

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Lucht MJ, Hoffman L, Haug S, Meyer C, Pussehl D, Quellmalz A, Klauer T, Grabe HJ, Freyberger HJ, John U, Schomerus G. A Surveillance Tool Using Mobile Phone Short Message Service to Reduce Alcohol Consumption Among Alcohol-Dependent Patients. Alcohol Clin Exp Res 2014;38:1728-36. [DOI: 10.1111/acer.12403] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2013] [Accepted: 02/01/2014] [Indexed: 11/30/2022]

Hallgren KA, Witkiewitz K. Missing data in alcohol clinical trials: a comparison of methods. Alcohol Clin Exp Res 2013;37:2152-60. [PMID: 23889334 PMCID: PMC4113114 DOI: 10.1111/acer.12205] [Citation(s) in RCA: 128] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2013] [Accepted: 04/27/2013] [Indexed: 11/30/2022]

Abstract

BACKGROUND

The rate of participant attrition in alcohol clinical trials is often substantial and can cause significant issues with regard to the handling of missing data in statistical analyses of treatment effects. It is common for researchers to assume that missing data is indicative of participant relapse, and under that assumption, many researchers have relied on setting all missing values to the worst-case scenario for the outcome (e.g., missing = heavy drinking). This sort of single-imputation method has been criticized for producing biased results in other areas of clinical research, but has not been evaluated within the context of alcohol clinical trials, and many alcohol researchers continue to use the missing = heavy drinking assumption.

METHODS

Data from the COMBINE study, a multisite randomized clinical trial, were used to generate simulated situations of missing data under a variety of conditions and assumptions. We manipulated the sample size (n = 200, 500, and 1,000) and dropout rate (5, 10, 25, 30%) under 3 missing data assumptions (missing completely at random, missing at random, and missing not at random). We then examined the association between receiving naltrexone and heavy drinking during the first 10 weeks following treatment using 5 methods for treating missing data (complete case analysis [CCA], last observation carried forward [LOCF], missing = heavy drinking, multiple imputation [MI], and full information maximum likelihood [FIML]).

RESULTS

CCA, LOCF, and missing = heavy drinking produced the most biased naltrexone effect estimates and standard errors under conditions that are likely to exist in randomized clinical trials. MI and FIML produced the least biased naltrexone effect estimates and standard errors.

CONCLUSIONS

Assuming that missing = heavy drinking produces biased results of the treatment effect and should not be used to evaluate treatment effects in alcohol clinical trials.

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Johnsen E, Jørgensen HA, Kroken RA, Løberg EM. Neurocognitive effectiveness of quetiapine, olanzapine, risperidone, and ziprasidone: a pragmatic, randomized trial. Eur Psychiatry 2011;28:174-84. [PMID: 22153730 DOI: 10.1016/j.eurpsy.2011.10.003] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/19/2011] [Revised: 10/10/2011] [Accepted: 10/12/2011] [Indexed: 02/01/2023] Open

Park MJ, Yamazaki Y, Yonekura Y, Yukawa K, Ishikawa H, Kiuchi T, Green J. Predicting complete loss to follow-up after a health-education program: number of absences and face-to-face contact with a researcher. BMC Med Res Methodol 2011;11:145. [PMID: 22032732 PMCID: PMC3215183 DOI: 10.1186/1471-2288-11-145] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2011] [Accepted: 10/27/2011] [Indexed: 12/02/2022] Open

Abstract

Background

Research on health-education programs requires longitudinal data. Loss to follow-up can lead to imprecision and bias, and complete loss to follow-up is particularly damaging. If that loss is predictable, then efforts to prevent it can be focused on those program participants who are at the highest risk. We identified predictors of complete loss to follow-up in a longitudinal cohort study.

Methods

Data were collected over 1 year in a study of adults with chronic illnesses who were in a program to learn self-management skills. Following baseline measurements, the program had one group-discussion session each week for six weeks. Follow-up questionnaires were sent 3, 6, and 12 months after the baseline measurement. A person was classified as completely lost to follow-up if none of those three follow-up questionnaires had been returned by two months after the last one was sent.

We tested two hypotheses: that complete loss to follow-up was directly associated with the number of absences from the program sessions, and that it was less common among people who had had face-to-face contact with one of the researchers. We also tested predictors of data loss identified previously and examined associations with specific diagnoses.

Using the unpaired t-test, the U test, Fisher's exact test, and logistic regression, we identified good predictors of complete loss to follow-up.

Results

The prevalence of complete loss to follow-up was 12.2% (50/409). Complete loss to follow-up was directly related to the number of absences (odds ratio; 95% confidence interval: 1.78; 1.49-2.12), and it was inversely related to age (0.97; 0.95-0.99). Complete loss to follow-up was less common among people who had met one of the researchers (0.51; 0.28-0.95) and among those with connective tissue disease (0.29; 0.09-0.98). For the multivariate logistic model the area under the ROC curve was 0.77.

Conclusions

Complete loss to follow-up after this health-education program can be predicted to some extent from data that are easy to collect (age, number of absences, and diagnosis). Also, face-to-face contact with a researcher deserves further study as a way of increasing participation in follow-up, and health-education programs should include it.

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Wilcox CE, Bogenschutz MP, Nakazawa M, Woody GE. Compensation effects on clinical trial data collection in opioid-dependent young adults. THE AMERICAN JOURNAL OF DRUG AND ALCOHOL ABUSE 2011;38:81-6. [PMID: 21936751 DOI: 10.3109/00952990.2011.600393] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]

Kjelby E, Jørgensen HA, Kroken RA, Løberg EM, Johnsen E. Anti-depressive effectiveness of olanzapine, quetiapine, risperidone and ziprasidone: a pragmatic, randomized trial. BMC Psychiatry 2011;11:145. [PMID: 21884578 PMCID: PMC3178484 DOI: 10.1186/1471-244x-11-145] [Citation(s) in RCA: 24] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/18/2011] [Accepted: 08/31/2011] [Indexed: 11/10/2022] Open

Abstract

BACKGROUND

Efficacy studies indicate anti-depressive effects of at least some second generation antipsychotics (SGAs). The Bergen Psychosis Project (BPP) is a 24-month, pragmatic, industry-independent, randomized, head-to-head comparison of olanzapine, quetiapine, risperidone and ziprasidone in patients acutely admitted with psychosis. The aim of the study is to investigate whether differential anti-depressive effectiveness exists among SGAs in a clinically relevant sample of patients acutely admitted with psychosis.

METHODS

Adult patients acutely admitted to an emergency ward for psychosis were randomized to olanzapine, quetiapine, risperidone or ziprasidone and followed for up to 2 years. Participants were assessed repeatedly using the Positive and Negative Syndrome Scale-Depression factor (PANSS-D) and the Calgary Depression Scale for Schizophrenia (CDSS).

RESULTS

A total of 226 patients were included. A significant time-effect showing a steady decline in depressive symptoms in all medication groups was demonstrated. There were no substantial differences among the SGAs in reducing the PANSS-D score or the CDSS sum score. Separate analyses of groups with CDSS sum scores > 6 or ≤6, respectively, reflecting degree of depressive morbidity, revealed essentially identical results to the primary analyses. There was a high correlation between the PANSS-D and the CDSS sum score (r = 0.77; p < 0.01).

CONCLUSIONS

There was no substantial difference in anti-depressive effectiveness among olanzapine, quetiapine, risperidone or ziprasidone in this clinically relevant sample of patients acutely admitted to hospital for symptoms of psychosis. Based on our findings we can make no recommendations concerning choice of any particular SGA for targeting symptoms of depression in a patient acutely admitted with psychosis.

TRIAL REGISTRATION

ClinicalTrials.gov ID; URL: http://www.clinicaltrials.gov/: NCT00932529.

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Farrokhyar F, Bajammal S, Kahnamoui K, Bhandari M. Practical tips for surgical research. Ensuring balanced groups in surgical trials. Can J Surg 2010;53:418-423. [PMID: 21092436 PMCID: PMC2993026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/27/2009] [Indexed: 05/30/2023] Open

McRae-Clark AL, Carter RE, Killeen TK, Carpenter MJ, White KG, Brady KT. A placebo-controlled trial of atomoxetine in marijuana-dependent individuals with attention deficit hyperactivity disorder. Am J Addict 2010;19:481-9. [PMID: 20958842 DOI: 10.1111/j.1521-0391.2010.00076.x] [Citation(s) in RCA: 53] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022] Open

Johnsen E, Kroken RA, Wentzel-Larsen T, Jørgensen HA. Effectiveness of second-generation antipsychotics: a naturalistic, randomized comparison of olanzapine, quetiapine, risperidone, and ziprasidone. BMC Psychiatry 2010;10:26. [PMID: 20334680 PMCID: PMC2851682 DOI: 10.1186/1471-244x-10-26] [Citation(s) in RCA: 46] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/24/2009] [Accepted: 03/24/2010] [Indexed: 12/15/2022] Open

Abstract

BACKGROUND

No clear recommendations exist regarding which antipsychotic drug should be prescribed first for a patient suffering from psychosis. The primary aims of this naturalistic study were to assess the head-to-head effectiveness of first-line second-generation antipsychotics with regards to time until drug discontinuation, duration of index admission, time until readmission, change of psychopathology scores and tolerability outcomes.

METHODS

Patients >or= 18 years of age admitted to the emergency ward for symptoms of psychosis were consecutively randomized to risperidone (n = 53), olanzapine (n = 52), quetiapine (n = 50), or ziprasidone (n = 58), and followed for up to 2 years.

RESULTS

A total of 213 patients were included, of which 68% were males. The sample represented a diverse population suffering from psychosis. At admittance the mean Positive and Negative Syndrome Scale (PANSS) total score was 74 points and 44% were antipsychotic drug naïve. The primary intention-to-treat analyses revealed no substantial differences between the drugs regarding the times until discontinuation of initial drug, until discharge from index admission, or until readmission. Quetiapine was superior to risperidone and olanzapine in reducing the PANSS total score and the positive subscore. Quetiapine was superior to the other drugs in decreasing the PANSS general psychopathology subscore; in decreasing the Clinical Global Impression - Severity of Illness scale score (CGI-S); and in increasing the Global Assessment of Functioning - Split version, Functions scale score (GAF-F). Ziprasidone was superior to risperidone in decreasing the PANSS positive symptoms subscore and the CGI-S score, and in increasing the GAF-F score. The drugs performed equally with regards to most tolerability outcomes except a higher increase of hip-circumference per day for olanzapine compared to risperidone, and more galactorrhoea for risperidone compared to the other groups.

CONCLUSIONS

Quetiapine appears to be a good starting drug candidate in this sample of patients admitted to hospital for symptoms of psychosis.

TRIAL REGISTRATION

ClinicalTrials.gov ID; URL: http://www.clinicaltrials.gov/: NCT00932529.

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