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1. Reproducible variability: assessing investigator discordance across 9 research teams attempting to reproduce the same observational study.

Author

Ostropolets, Anna, Albogami, Yasser, Conover, Mitchell, Banda, Juan, Baumgartner, William, Blacketer, Clair, Desai, Priyamvada, DuVall, Scott, Fortin, Stephen, Gilbert, James, Golozar, Asieh, Ide, Joshua, Kanter, Andrew, Kern, David, Kim, Chungsoo, Lai, Lana, Li, Chenyu, Liu, Feifan, Lynch, Kristine, Minty, Evan, Neves, Maria, Ng, Ding, Obene, Tontel, Pera, Victor, Pratt, Nicole, Rao, Gowtham, Rappoport, Nadav, Reinecke, Ines, Saroufim, Paola, Shoaibi, Azza, Simon, Katherine, Swerdel, Joel, Voss, Erica, Weaver, James, Zhang, Linying, Hripcsak, George, Ryan, Patrick, and Suchard, Marc

Subjects
credibility, observational data, open science, reproducibility, Humans, Research Personnel, Databases, Factual
Abstract

OBJECTIVE: Observational studies can impact patient care but must be robust and reproducible. Nonreproducibility is primarily caused by unclear reporting of design choices and analytic procedures. This study aimed to: (1) assess how the study logic described in an observational study could be interpreted by independent researchers and (2) quantify the impact of interpretations variability on patient characteristics. MATERIALS AND METHODS: Nine teams of highly qualified researchers reproduced a cohort from a study by Albogami et al. The teams were provided the clinical codes and access to the tools to create cohort definitions such that the only variable part was their logic choices. We executed teams cohort definitions against the database and compared the number of subjects, patient overlap, and patient characteristics. RESULTS: On average, the teams interpretations fully aligned with the master implementation in 4 out of 10 inclusion criteria with at least 4 deviations per team. Cohorts size varied from one-third of the master cohort size to 10 times the cohort size (2159-63 619 subjects compared to 6196 subjects). Median agreement was 9.4% (interquartile range 15.3-16.2%). The teams cohorts significantly differed from the master implementation by at least 2 baseline characteristics, and most of the teams differed by at least 5. CONCLUSIONS: Independent research teams attempting to reproduce the study based on its free-text description alone produce different implementations that vary in the population size and composition. Sharing analytical code supported by a common data model and open-source tools allows reproducing a study unambiguously thereby preserving initial design choices.

Published
2023

2. CohortDiagnostics: Phenotype evaluation across a network of observational data sources using population-level characterization.

Author

Rao, Gowtham A., Shoaibi, Azza, Makadia, Rupa, Hardin, Jill, Swerdel, Joel, Weaver, James, Voss, Erica A., Conover, Mitchell M., Fortin, Stephen, Sena, Anthony G., Knoll, Chris, Hughes, Nigel, Gilbert, James P., Blacketer, Clair, Andryc, Alan, DeFalco, Frank, Molinaro, Anthony, Reps, Jenna, Schuemie, Martijn J., and Ryan, Patrick B.

Subjects
SYSTEMIC lupus erythematosus, ALZHEIMER'S disease, PHENOTYPES, DIAGNOSIS, ALGORITHMS
Abstract

Objective: This paper introduces a novel framework for evaluating phenotype algorithms (PAs) using the open-source tool, Cohort Diagnostics. Materials and methods: The method is based on several diagnostic criteria to evaluate a patient cohort returned by a PA. Diagnostics include estimates of incidence rate, index date entry code breakdown, and prevalence of all observed clinical events prior to, on, and after index date. We test our framework by evaluating one PA for systemic lupus erythematosus (SLE) and two PAs for Alzheimer's disease (AD) across 10 different observational data sources. Results: By utilizing CohortDiagnostics, we found that the population-level characteristics of individuals in the cohort of SLE closely matched the disease's anticipated clinical profile. Specifically, the incidence rate of SLE was consistently higher in occurrence among females. Moreover, expected clinical events like laboratory tests, treatments, and repeated diagnoses were also observed. For AD, although one PA identified considerably fewer patients, absence of notable differences in clinical characteristics between the two cohorts suggested similar specificity. Discussion: We provide a practical and data-driven approach to evaluate PAs, using two clinical diseases as examples, across a network of OMOP data sources. Cohort Diagnostics can ensure the subjects identified by a specific PA align with those intended for inclusion in a research study. Conclusion: Diagnostics based on large-scale population-level characterization can offer insights into the misclassification errors of PAs. [ABSTRACT FROM AUTHOR]

Published
2025
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3. Research Protocol for an Observational Health Data Analysis on the Adverse Events of Systemic Treatment in Patients with Metastatic Hormone-sensitive Prostate Cancer: Big Data Analytics Using the PIONEER Platform

Author

Rajwa, Pawel, primary, Borkowetz, Angelika, additional, Abbott, Thomas, additional, Alberti, Andrea, additional, Bjartell, Anders, additional, Brash, James T., additional, Campi, Riccardo, additional, Chilelli, Andrew, additional, Conover, Mitchell, additional, Constantinovici, Niculae, additional, Davies, Eleanor, additional, De Meulder, Bertrand, additional, Eid, Sherrine, additional, Gacci, Mauro, additional, Golozar, Asieh, additional, Hafeez, Haroon, additional, Haque, Samiul, additional, Hijazy, Ayman, additional, Hulsen, Tim, additional, Josefsson, Andreas, additional, Khalid, Sara, additional, Kolde, Raivo, additional, Kotik, Daniel, additional, Kurki, Samu, additional, Lambrecht, Mark, additional, Leung, Chi-Ho, additional, Moreno, Julia, additional, Nicoletti, Rossella, additional, Nieboer, Daan, additional, Oja, Marek, additional, Palanisamy, Soundarya, additional, Prinsen, Peter, additional, Reich, Christian, additional, Raffaele Resta, Giulio, additional, Ribal, Maria J., additional, Gómez Rivas, Juan, additional, Smith, Emma, additional, Snijder, Robert, additional, Steinbeisser, Carl, additional, Vandenberghe, Frederik, additional, Cornford, Philip, additional, Evans-Axelsson, Susan, additional, N'Dow, James, additional, and Willemse, Peter-Paul M., additional

Published
2024
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4. Renin–angiotensin system blockers and susceptibility to COVID-19: an international, open science, cohort analysis

Author

Morales, Daniel R, Conover, Mitchell M, You, Seng Chan, Pratt, Nicole, Kostka, Kristin, Duarte-Salles, Talita, Fernández-Bertolín, Sergio, Aragón, Maria, DuVall, Scott L, Lynch, Kristine, Falconer, Thomas, van Bochove, Kees, Sung, Cynthia, Matheny, Michael E, Lambert, Christophe G, Nyberg, Fredrik, Alshammari, Thamir M, Williams, Andrew E, Park, Rae Woong, Weaver, James, Sena, Anthony G, Schuemie, Martijn J, Rijnbeek, Peter R, Williams, Ross D, Lane, Jennifer C E, Prats-Uribe, Albert, Zhang, Lin, Areia, Carlos, Krumholz, Harlan M, Prieto-Alhambra, Daniel, Ryan, Patrick B, Hripcsak, George, and Suchard, Marc A

Published
2021
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5. Research protocol for an observational health data analysis on the adverse events of systemic treatment in patients with metastatic hormone-sensitive prostate cancer : big data analytics using the PIONEER platform

Author

Rajwa, Pawel, Borkowetz, Angelika, Abbott, Thomas, Alberti, Andrea, Bjartell, Anders, Brash, James T., Campi, Riccardo, Chilelli, Andrew, Conover, Mitchell, Constantinovici, Niculae, Davies, Eleanor, De Meulder, Bertrand, Eid, Sherrine, Gacci, Mauro, Golozar, Asieh, Hafeez, Haroon, Haque, Samiul, Hijazy, Ayman, Hulsen, Tim, Josefsson, Andreas, Khalid, Sara, Kolde, Raivo, Kotik, Daniel, Kurki, Samu, Lambrecht, Mark, Leung, Chi-Ho, Moreno, Julia, Nicoletti, Rossella, Nieboer, Daan, Oja, Marek, Palanisamy, Soundarya, Prinsen, Peter, Reich, Christian, Raffaele Resta, Giulio, Ribal, Maria J., Gómez Rivas, Juan, Smith, Emma, Snijder, Robert, Steinbeisser, Carl, Vandenberghe, Frederik, Cornford, Philip, Evans-Axelsson, Susan, N'Dow, James, Willemse, Peter-Paul M., Rajwa, Pawel, Borkowetz, Angelika, Abbott, Thomas, Alberti, Andrea, Bjartell, Anders, Brash, James T., Campi, Riccardo, Chilelli, Andrew, Conover, Mitchell, Constantinovici, Niculae, Davies, Eleanor, De Meulder, Bertrand, Eid, Sherrine, Gacci, Mauro, Golozar, Asieh, Hafeez, Haroon, Haque, Samiul, Hijazy, Ayman, Hulsen, Tim, Josefsson, Andreas, Khalid, Sara, Kolde, Raivo, Kotik, Daniel, Kurki, Samu, Lambrecht, Mark, Leung, Chi-Ho, Moreno, Julia, Nicoletti, Rossella, Nieboer, Daan, Oja, Marek, Palanisamy, Soundarya, Prinsen, Peter, Reich, Christian, Raffaele Resta, Giulio, Ribal, Maria J., Gómez Rivas, Juan, Smith, Emma, Snijder, Robert, Steinbeisser, Carl, Vandenberghe, Frederik, Cornford, Philip, Evans-Axelsson, Susan, N'Dow, James, and Willemse, Peter-Paul M.

Abstract

Combination therapies in metastatic hormone-sensitive prostate cancer (mHSPC), which include the addition of an androgen receptor signaling inhibitor and/or docetaxel to androgen deprivation therapy, have been a game changer in the management of this disease stage. However, these therapies come with their fair share of toxicities and side effects. The goal of this observational study is to report drug-related adverse events (AEs), which are correlated with systemic combination therapies for mHSPC. Determining the optimal treatment option requires large cohorts to estimate the tolerability and AEs of these combination therapies in “real-life” patients with mHSPC, as provided in this study. We use a network of databases that includes population-based registries, electronic health records, and insurance claims, containing the overall target population and subgroups of patients defined by unique certain characteristics, demographics, and comorbidities, to compute the incidence of common AEs associated with systemic therapies in the setting of mHSPC. These data sources are standardised using the Observational Medical Outcomes Partnership Common Data Model. We perform the descriptive statistics as well as calculate the AE incidence rate separately for each treatment group, stratified by age groups and index year. The time until the first event is estimated using the Kaplan-Meier method within each age group. In the case of episodic events, the anticipated mean cumulative counts of events are calculated. Our study will allow clinicians to tailor optimal therapies for mHSPC patients, and they will serve as a basis for comparative method studies.

Published
2024
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6. Research Protocol for an Observational Health Data Analysis on the Adverse Events of Systemic Treatment in Patients with Metastatic Hormone-sensitive Prostate Cancer: Big Data Analytics Using the PIONEER Platform

Author

MS Urologische Oncologie, Cancer, Rajwa, Pawel, Borkowetz, Angelika, Abbott, Thomas, Alberti, Andrea, Bjartell, Anders, Brash, James T, Campi, Riccardo, Chilelli, Andrew, Conover, Mitchell, Constantinovici, Niculae, Davies, Eleanor, De Meulder, Bertrand, Eid, Sherrine, Gacci, Mauro, Golozar, Asieh, Hafeez, Haroon, Haque, Samiul, Hijazy, Ayman, Hulsen, Tim, Josefsson, Andreas, Khalid, Sara, Kolde, Raivo, Kotik, Daniel, Kurki, Samu, Lambrecht, Mark, Leung, Chi-Ho, Moreno, Julia, Nicoletti, Rossella, Nieboer, Daan, Oja, Marek, Palanisamy, Soundarya, Prinsen, Peter, Reich, Christian, Raffaele Resta, Giulio, Ribal, Maria J, Gómez Rivas, Juan, Smith, Emma, Snijder, Robert, Steinbeisser, Carl, Vandenberghe, Frederik, Cornford, Philip, Evans-Axelsson, Susan, N'Dow, James, Willemse, Peter-Paul M, MS Urologische Oncologie, Cancer, Rajwa, Pawel, Borkowetz, Angelika, Abbott, Thomas, Alberti, Andrea, Bjartell, Anders, Brash, James T, Campi, Riccardo, Chilelli, Andrew, Conover, Mitchell, Constantinovici, Niculae, Davies, Eleanor, De Meulder, Bertrand, Eid, Sherrine, Gacci, Mauro, Golozar, Asieh, Hafeez, Haroon, Haque, Samiul, Hijazy, Ayman, Hulsen, Tim, Josefsson, Andreas, Khalid, Sara, Kolde, Raivo, Kotik, Daniel, Kurki, Samu, Lambrecht, Mark, Leung, Chi-Ho, Moreno, Julia, Nicoletti, Rossella, Nieboer, Daan, Oja, Marek, Palanisamy, Soundarya, Prinsen, Peter, Reich, Christian, Raffaele Resta, Giulio, Ribal, Maria J, Gómez Rivas, Juan, Smith, Emma, Snijder, Robert, Steinbeisser, Carl, Vandenberghe, Frederik, Cornford, Philip, Evans-Axelsson, Susan, N'Dow, James, and Willemse, Peter-Paul M

Published
2024

7. Research Protocol for an Observational Health Data Analysis on the Adverse Events of Systemic Treatment in Patients with Metastatic Hormone-sensitive Prostate Cancer:Big Data Analytics Using the PIONEER Platform

Author

Rajwa, Pawel, Borkowetz, Angelika, Abbott, Thomas, Alberti, Andrea, Bjartell, Anders, Brash, James T., Campi, Riccardo, Chilelli, Andrew, Conover, Mitchell, Constantinovici, Niculae, Davies, Eleanor, De Meulder, Bertrand, Eid, Sherrine, Gacci, Mauro, Golozar, Asieh, Hafeez, Haroon, Haque, Samiul, Hijazy, Ayman, Hulsen, Tim, Josefsson, Andreas, Khalid, Sara, Kolde, Raivo, Kotik, Daniel, Kurki, Samu, Lambrecht, Mark, Leung, Chi Ho, Moreno, Julia, Nicoletti, Rossella, Nieboer, Daan, Oja, Marek, Palanisamy, Soundarya, Prinsen, Peter, Reich, Christian, Raffaele Resta, Giulio, Ribal, Maria J., Gómez Rivas, Juan, Smith, Emma, Snijder, Robert, Steinbeisser, Carl, Vandenberghe, Frederik, Cornford, Philip, Evans-Axelsson, Susan, N'Dow, James, Willemse, Peter Paul M., Rajwa, Pawel, Borkowetz, Angelika, Abbott, Thomas, Alberti, Andrea, Bjartell, Anders, Brash, James T., Campi, Riccardo, Chilelli, Andrew, Conover, Mitchell, Constantinovici, Niculae, Davies, Eleanor, De Meulder, Bertrand, Eid, Sherrine, Gacci, Mauro, Golozar, Asieh, Hafeez, Haroon, Haque, Samiul, Hijazy, Ayman, Hulsen, Tim, Josefsson, Andreas, Khalid, Sara, Kolde, Raivo, Kotik, Daniel, Kurki, Samu, Lambrecht, Mark, Leung, Chi Ho, Moreno, Julia, Nicoletti, Rossella, Nieboer, Daan, Oja, Marek, Palanisamy, Soundarya, Prinsen, Peter, Reich, Christian, Raffaele Resta, Giulio, Ribal, Maria J., Gómez Rivas, Juan, Smith, Emma, Snijder, Robert, Steinbeisser, Carl, Vandenberghe, Frederik, Cornford, Philip, Evans-Axelsson, Susan, N'Dow, James, and Willemse, Peter Paul M.

Abstract

Combination therapies in metastatic hormone-sensitive prostate cancer (mHSPC), which include the addition of an androgen receptor signaling inhibitor and/or docetaxel to androgen deprivation therapy, have been a game changer in the management of this disease stage. However, these therapies come with their fair share of toxicities and side effects. The goal of this observational study is to report drug-related adverse events (AEs), which are correlated with systemic combination therapies for mHSPC. Determining the optimal treatment option requires large cohorts to estimate the tolerability and AEs of these combination therapies in “real-life” patients with mHSPC, as provided in this study. We use a network of databases that includes population-based registries, electronic health records, and insurance claims, containing the overall target population and subgroups of patients defined by unique certain characteristics, demographics, and comorbidities, to compute the incidence of common AEs associated with systemic therapies in the setting of mHSPC. These data sources are standardised using the Observational Medical Outcomes Partnership Common Data Model. We perform the descriptive statistics as well as calculate the AE incidence rate separately for each treatment group, stratified by age groups and index year. The time until the first event is estimated using the Kaplan-Meier method within each age group. In the case of episodic events, the anticipated mean cumulative counts of events are calculated. Our study will allow clinicians to tailor optimal therapies for mHSPC patients, and they will serve as a basis for comparative method studies.

Published
2024

10. International cohort study indicates no association between alpha-1 blockers and susceptibility to COVID-19 in benign prostatic hyperplasia patients

Author

Nishimura, Akihiko, primary, Xie, Junqing, additional, Kostka, Kristin, additional, Duarte-Salles, Talita, additional, Fernández Bertolín, Sergio, additional, Aragón, María, additional, Blacketer, Clair, additional, Shoaibi, Azza, additional, DuVall, Scott L., additional, Lynch, Kristine, additional, Matheny, Michael E., additional, Falconer, Thomas, additional, Morales, Daniel R., additional, Conover, Mitchell M., additional, Chan You, Seng, additional, Pratt, Nicole, additional, Weaver, James, additional, Sena, Anthony G., additional, Schuemie, Martijn J., additional, Reps, Jenna, additional, Reich, Christian, additional, Rijnbeek, Peter R., additional, Ryan, Patrick B., additional, Hripcsak, George, additional, Prieto-Alhambra, Daniel, additional, and Suchard, Marc A., additional

Published
2022
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11. International cohort study indicates no association between alpha-1 blockers and susceptibility to COVID-19 in benign prostatic hyperplasia patients

Author

Nishimura, Akihiko, Xie, Junqing, Kostka, Kristin, Duarte-Salles, Talita, Bertolin, Sergio Fernandez, Aragon, Maria, Blacketer, Clair, Shoaibi, Azza, DuVall, Scott L., Lynch, Kristine, Matheny, Michael E., Falconer, Thomas, Morales, Daniel R., Conover, Mitchell M., You, Seng Chan, Pratt, Nicole, Weaver, James, Sena, Anthony G., Schuemie, Martijn J., Reps, Jenna, Reich, Christian, Rijnbeek, Peter R., Ryan, Patrick B., Hripcsak, George, Prieto-Alhambra, Daniel, Suchard, Marc A., Nishimura, Akihiko, Xie, Junqing, Kostka, Kristin, Duarte-Salles, Talita, Bertolin, Sergio Fernandez, Aragon, Maria, Blacketer, Clair, Shoaibi, Azza, DuVall, Scott L., Lynch, Kristine, Matheny, Michael E., Falconer, Thomas, Morales, Daniel R., Conover, Mitchell M., You, Seng Chan, Pratt, Nicole, Weaver, James, Sena, Anthony G., Schuemie, Martijn J., Reps, Jenna, Reich, Christian, Rijnbeek, Peter R., Ryan, Patrick B., Hripcsak, George, Prieto-Alhambra, Daniel, and Suchard, Marc A.

Abstract

Purpose: Alpha-1 blockers, often used to treat benign prostatic hyperplasia (BPH), have been hypothesized to prevent COVID-19 complications by minimising cytokine storm release. The proposed treatment based on this hypothesis currently lacks support from reliable real-world evidence, however. We leverage an international network of large-scale healthcare databases to generate comprehensive evidence in a transparent and reproducible manner. Methods: In this international cohort study, we deployed electronic health records from Spain (SIDIAP) and the United States (Department of Veterans Affairs, Columbia University Irving Medical Center, IQVIA OpenClaims, Optum DOD, Optum EHR). We assessed association between alpha-1 blocker use and risks of three COVID-19 outcomes-diagnosis, hospitalization, and hospitalization requiring intensive services-using a prevalent-user active-comparator design. We estimated hazard ratios using state-of-the-art techniques to minimize potential confounding, including large-scale propensity score matching/stratification and negative control calibration. We pooled database-specific estimates through random effects meta-analysis. Results: Our study overall included 2.6 and 0.46 million users of alpha-1 blockers and of alternative BPH medications. We observed no significant difference in their risks for any of the COVID-19 outcomes, with our meta-analytic HR estimates being 1.02 (95% CI: 0.92-1.13) for diagnosis, 1.00 (95% CI: 0.89-1.13) for hospitalization, and 1.15 (95% CI: 0.71-1.88) for hospitalization requiring intensive services. Conclusion: We found no evidence of the hypothesized reduction in risks of the COVID-19 outcomes from the prevalent-use of alpha-1 blockers-further research is needed to identify effective therapies for this novel disease.

Published
2022

12. International cohort study indicates no association between alpha-1 blockers and susceptibility to COVID-19 in benign prostatic hyperplasia patients.

Author

Akihiko Nishimura, Junqing Xie, Kostka, Kristin, Duarte-Salles, Talita, Bertolín, Sergio Fernández, Aragón, María, Blacketer, Clair, Shoaibi, Azza, DuVall, Scott L., Lynch, Kristine, Matheny, Michael E., Falconer, Thomas, Morales, Daniel R., Conover, Mitchell M., Seng Chan You, Pratt, Nicole, Weaver, James, Sena, Anthony G., Schuemie, Martijn J., and Reps, Jenna

Subjects
BENIGN prostatic hyperplasia, COVID-19, ELECTRONIC health records, PROPENSITY score matching, COHORT analysis
Abstract

Purpose: Alpha-1 blockers, often used to treat benign prostatic hyperplasia (BPH), have been hypothesized to prevent COVID-19 complications by minimising cytokine storm release. The proposed treatment based on this hypothesis currently lacks support from reliable real-world evidence, however. We leverage an international network of large-scale healthcare databases to generate comprehensive evidence in a transparent and reproducible manner. Methods: In this international cohort study, we deployed electronic health records from Spain (SIDIAP) and the United States (Department of Veterans Affairs, Columbia University Irving Medical Center, IQVIA OpenClaims, Optum DOD, Optum EHR). We assessed association between alpha-1 blocker use and risks of three COVID-19 outcomes--diagnosis, hospitalization, and hospitalization requiring intensive services--using a prevalent-user activecomparator design. We estimated hazard ratios using state-of-the-art techniques to minimize potential confounding, including large-scale propensity score matching/stratification and negative control calibration. We pooled database-specific estimates through random effects meta-analysis. Results: Our study overall included 2.6 and 0.46 million users of alpha-1 blockers and of alternative BPH medications. We observed no significant difference in their risks for any of the COVID-19 outcomes, with our metaanalytic HR estimates being 1.02 (95% CI: 0.92-1.13) for diagnosis, 1.00 (95% CI: 0.89-1.13) for hospitalization, and 1.15 (95% CI: 0.71-1.88) for hospitalization requiring intensive services. Conclusion: We found no evidence of the hypothesized reduction in risks of the COVID-19 outcomes from the prevalent-use of alpha-1 blockers--further research is needed to identify effective therapies for this novel disease. [ABSTRACT FROM AUTHOR]

Published
2022
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13. Risk of hydroxychloroquine alone and in combination with azithromycin in the treatment of rheumatoid arthritis:a multinational, retrospective study

Author

Lane, Jennifer C E, Weaver, James, Kostka, Kristin, Duarte-Salles, Talita, Abrahao, Maria Tereza F, Alghoul, Heba, Alser, Osaid, Alshammari, Thamir M, Biedermann, Patricia, Banda, Juan M, Burn, Edward, Casajust, Paula, Conover, Mitchell M, Culhane, Aedin C, Davydov, Alexander, DuVall, Scott L, Dymshyts, Dmitry, Fernandez-Bertolin, Sergio, Fišter, Kristina, Hardin, Jill, Hester, Laura, Hripcsak, George, Kaas-Hansen, Benjamin Skov, Kent, Seamus, Khosla, Sajan, Kolovos, Spyros, Lambert, Christophe G, van der Lei, Johan, Lynch, Kristine E, Makadia, Rupa, Margulis, Andrea V, Matheny, Michael E, Mehta, Paras, Morales, Daniel R, Morgan-Stewart, Henry, Mosseveld, Mees, Newby, Danielle, Nyberg, Fredrik, Ostropolets, Anna, Park, Rae Woong, Prats-Uribe, Albert, Rao, Gowtham A, Reich, Christian, Reps, Jenna, Rijnbeek, Peter, Sathappan, Selva Muthu Kumaran, Schuemie, Martijn, Seager, Sarah, Sena, Anthony G, Shoaibi, Azza, Lane, Jennifer C E, Weaver, James, Kostka, Kristin, Duarte-Salles, Talita, Abrahao, Maria Tereza F, Alghoul, Heba, Alser, Osaid, Alshammari, Thamir M, Biedermann, Patricia, Banda, Juan M, Burn, Edward, Casajust, Paula, Conover, Mitchell M, Culhane, Aedin C, Davydov, Alexander, DuVall, Scott L, Dymshyts, Dmitry, Fernandez-Bertolin, Sergio, Fišter, Kristina, Hardin, Jill, Hester, Laura, Hripcsak, George, Kaas-Hansen, Benjamin Skov, Kent, Seamus, Khosla, Sajan, Kolovos, Spyros, Lambert, Christophe G, van der Lei, Johan, Lynch, Kristine E, Makadia, Rupa, Margulis, Andrea V, Matheny, Michael E, Mehta, Paras, Morales, Daniel R, Morgan-Stewart, Henry, Mosseveld, Mees, Newby, Danielle, Nyberg, Fredrik, Ostropolets, Anna, Park, Rae Woong, Prats-Uribe, Albert, Rao, Gowtham A, Reich, Christian, Reps, Jenna, Rijnbeek, Peter, Sathappan, Selva Muthu Kumaran, Schuemie, Martijn, Seager, Sarah, Sena, Anthony G, and Shoaibi, Azza

Abstract

Background: Hydroxychloroquine, a drug commonly used in the treatment of rheumatoid arthritis, has received much negative publicity for adverse events associated with its authorisation for emergency use to treat patients with COVID-19 pneumonia. We studied the safety of hydroxychloroquine, alone and in combination with azithromycin, to determine the risk associated with its use in routine care in patients with rheumatoid arthritis.Methods: In this multinational, retrospective study, new user cohort studies in patients with rheumatoid arthritis aged 18 years or older and initiating hydroxychloroquine were compared with those initiating sulfasalazine and followed up over 30 days, with 16 severe adverse events studied. Self-controlled case series were done to further establish safety in wider populations, and included all users of hydroxychloroquine regardless of rheumatoid arthritis status or indication. Separately, severe adverse events associated with hydroxychloroquine plus azithromycin (compared with hydroxychloroquine plus amoxicillin) were studied. Data comprised 14 sources of claims data or electronic medical records from Germany, Japan, the Netherlands, Spain, the UK, and the USA. Propensity score stratification and calibration using negative control outcomes were used to address confounding. Cox models were fitted to estimate calibrated hazard ratios (HRs) according to drug use. Estimates were pooled where the I2 value was less than 0·4.Findings: The study included 956 374 users of hydroxychloroquine, 310 350 users of sulfasalazine, 323 122 users of hydroxychloroquine plus azithromycin, and 351 956 users of hydroxychloroquine plus amoxicillin. No excess risk of severe adverse events was identified when 30-day hydroxychloroquine and sulfasalazine use were compared. Self-controlled case series confirmed these findings. However, long-term use of hydroxychloroquine appeared to be associated with increased cardiovascular mortality (calibrated HR 1

Published
2020

15. Incidence of opioid-managed pelvic pain after hysteroscopic sterilization versus laparoscopic sterilization, U.S. 2005-2012

Author

Conover, Mitchell M., Howell, Jennifer O., Wu, Jennifer M., Kinlaw, Alan C., Dasgupta, Nabarun, and Funk, Michele Jonsson

Subjects
Adult, Pain, Postoperative, Time Factors, Adolescent, Databases, Factual, Sterilization, Tubal, Incidence, Pharmacoepidemiology, Hysteroscopy, Middle Aged, Pelvic Pain, Severity of Illness Index, Article, United States, Analgesics, Opioid, Young Adult, Treatment Outcome, Humans, Female, Laparoscopy, Propensity Score, Pain Measurement, Proportional Hazards Models
Abstract

Compare incidence of opioid-managed pelvic pain within 12 months after hysteroscopic and laparoscopic sterilization.Using administrative claims, we identified women aged 18-49 years without recent history of childbirth who underwent hysteroscopic or laparoscopic sterilization between 2005 and 2012. We defined the outcome as ≥2 diagnoses for pelvic pain and ≥2 prescription fills for opioids. We calculated adjusted hazard ratios (HR) using Cox models and propensity score methods (matching and inverse-probability-of-treatment-weighting [IPTW]).We identified 71,875 eligible women (hysteroscopic n = 26,927 [37.5%], laparoscopic n = 44,948 [62.5%]). Of those, 236 (0.88%) hysteroscopic patients and 420 (0.93%) laparoscopic patients experienced the outcome (crude HR = 0.97, 95%CI: [0.83, 1.14]). Adjusted analyses also yielded near-null results (matched HR = 1.08, 95%CI [0.90, 1.31]; IPTW HR = 0.97, 95%CI [0.80, 1.18]). While most sensitivity analyses generated results close to the null, hazard ratios estimated using propensity score matching ranged from 0.65 to 1.53.Among women without recent history of childbirth, we did not find compelling evidence of a clinically meaningful increase in the incidence of pelvic pain requiring opioids during the year after hysteroscopic sterilization. However, effects observed in sensitivity analyses may merit further investigation.

Published
2015

16. An Analysis of the Cross Section of Returns for EREITs Using a Varying-Risk Beta Model

Author

Conover, Mitchell C., Friday, H. Swint, and Howton, Shelly W.

Subjects
Rate of return -- Models -- Usage -- Economic aspects, Economics -- Models -- Usage -- Economic aspects, Econometrics -- Usage -- Economic aspects -- Models, Real estate investment trusts -- History -- Usage, Real estate industry -- Economic aspects -- History -- Models -- Usage, Business, Economics, Real estate industry, Return on investment, Economic aspects, Usage, Models, History
Abstract

Mitchell C. Conover [*] H. Swint Friday [**] Shelly W. Howton [***] A dual-beta asset pricing model is employed to examine the cross-section of realized equity real estate investment trust [...]

Published
2000

19. Reproducible variability: assessing investigator discordance across 9 research teams attempting to reproduce the same observational study

Author

Anna Ostropolets, Yasser Albogami, Mitchell Conover, Juan M Banda, William A Baumgartner, Clair Blacketer, Priyamvada Desai, Scott L DuVall, Stephen Fortin, James P Gilbert, Asieh Golozar, Joshua Ide, Andrew S Kanter, David M Kern, Chungsoo Kim, Lana Y H Lai, Chenyu Li, Feifan Liu, Kristine E Lynch, Evan Minty, Maria Inês Neves, Ding Quan Ng, Tontel Obene, Victor Pera, Nicole Pratt, Gowtham Rao, Nadav Rappoport, Ines Reinecke, Paola Saroufim, Azza Shoaibi, Katherine Simon, Marc A Suchard, Joel N Swerdel, Erica A Voss, James Weaver, Linying Zhang, George Hripcsak, Patrick B Ryan, Medical Informatics, Ostropolets, Anna, Albogami, Yasser, Conover, Mitchell, Banda, Juan M, Pratt, Nicole, and Ryan, Patrick B

Subjects
observational data, open science, Health Informatics, reproducibility, credibility
Abstract

Objective Observational studies can impact patient care but must be robust and reproducible. Nonreproducibility is primarily caused by unclear reporting of design choices and analytic procedures. This study aimed to: (1) assess how the study logic described in an observational study could be interpreted by independent researchers and (2) quantify the impact of interpretations’ variability on patient characteristics. Materials and Methods Nine teams of highly qualified researchers reproduced a cohort from a study by Albogami et al. The teams were provided the clinical codes and access to the tools to create cohort definitions such that the only variable part was their logic choices. We executed teams’ cohort definitions against the database and compared the number of subjects, patient overlap, and patient characteristics. Results On average, the teams’ interpretations fully aligned with the master implementation in 4 out of 10 inclusion criteria with at least 4 deviations per team. Cohorts’ size varied from one-third of the master cohort size to 10 times the cohort size (2159–63 619 subjects compared to 6196 subjects). Median agreement was 9.4% (interquartile range 15.3–16.2%). The teams’ cohorts significantly differed from the master implementation by at least 2 baseline characteristics, and most of the teams differed by at least 5. Conclusions Independent research teams attempting to reproduce the study based on its free-text description alone produce different implementations that vary in the population size and composition. Sharing analytical code supported by a common data model and open-source tools allows reproducing a study unambiguously thereby preserving initial design choices.

Published
2023

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