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1. Deep phenotyping of 34,128 adult patients hospitalised with COVID-19 in an international network study

Author

Burn, E., You, S.C., Sena, A.G., Kostka, K., Abedtash, H., Abrahao, M.T.F., Alberga, A., Alghoul, H., Alser, O., Alshammari, T.M., Aragon, M, Areia, C., Banda, J.M., Cho, J. (Jeiwon), Culhane, A.C., Davydov, A., DeFalco, F.J., Duarte-Salles, T., DuVall, S., Falconer, T., Fernandez-Bertolin, S., Gao, W.H., Golozar, A., Hardin, J., Hripcsak, G. (G.), Huser, V, Jeon, H., Jing, Y.H., Jung, C.Y., Kaas-Hansen, B.S., Kaduk, D., Kent, S., Kim, Y., Kolovos, S., Lane, J.C.E., Lee, H. (Hang), Lynch, K.E., Makadia, R., Matheny, M.E., Mehta, P.P., Morales, D.R., Natarajan, K., Nyberg, F. (Fredrik), Ostropolets, A., Park, RW, Park, J. (Judy), Posada, J.D., Prats-Uribe, A., Rao, G., Reich, C., Rho, Y., Rijnbeek, P.R. (Peter), Schilling, LM, Schuemie, M.J. (Martijn), Shah, NH, Shoaibi, A., Song, S., Spotnitz, M., Suchard, M.A. (Marc), Swerdel, J.N., Vizcaya, D., Volpe, S., Wen, H.N., Williams, A.E., Yimer, B.B., Zhang, L., Zhuk, O., Prieto-Alhambra, D., Ryan, P., Burn, E., You, S.C., Sena, A.G., Kostka, K., Abedtash, H., Abrahao, M.T.F., Alberga, A., Alghoul, H., Alser, O., Alshammari, T.M., Aragon, M, Areia, C., Banda, J.M., Cho, J. (Jeiwon), Culhane, A.C., Davydov, A., DeFalco, F.J., Duarte-Salles, T., DuVall, S., Falconer, T., Fernandez-Bertolin, S., Gao, W.H., Golozar, A., Hardin, J., Hripcsak, G. (G.), Huser, V, Jeon, H., Jing, Y.H., Jung, C.Y., Kaas-Hansen, B.S., Kaduk, D., Kent, S., Kim, Y., Kolovos, S., Lane, J.C.E., Lee, H. (Hang), Lynch, K.E., Makadia, R., Matheny, M.E., Mehta, P.P., Morales, D.R., Natarajan, K., Nyberg, F. (Fredrik), Ostropolets, A., Park, RW, Park, J. (Judy), Posada, J.D., Prats-Uribe, A., Rao, G., Reich, C., Rho, Y., Rijnbeek, P.R. (Peter), Schilling, LM, Schuemie, M.J. (Martijn), Shah, NH, Shoaibi, A., Song, S., Spotnitz, M., Suchard, M.A. (Marc), Swerdel, J.N., Vizcaya, D., Volpe, S., Wen, H.N., Williams, A.E., Yimer, B.B., Zhang, L., Zhuk, O., Prieto-Alhambra, D., and Ryan, P.

Published
2020
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2. Comparative safety and effectiveness of alendronate versus raloxifene in women with osteoporosis

Author

Kim, Y. (Yeesuk), Tian, Y. (Yuxi), Yang, J. (Jianxiao), Huser, V. (Vojtech), Jin, P. (Peng), Lambert, C.G. (Christophe G.), Park, H. (Hojun), You, S.C. (Seng Chan), Park, R.W. (Rae Woong), Rijnbeek, P.R. (Peter), Van Zandt, M. (Mui), Reich, C. (Christian), Vashisht, R. (Rohit), Wu, Y. (Yonghui), Duke, J.D. (Jon D.), Hripcsak, G. (G.), Madigan, D. (David), Shah, N.H. (Nigam H.), Ryan, P.B. (Patrick), Schuemie, M.J. (Martijn), Suchard, M.A. (Marc), Kim, Y. (Yeesuk), Tian, Y. (Yuxi), Yang, J. (Jianxiao), Huser, V. (Vojtech), Jin, P. (Peng), Lambert, C.G. (Christophe G.), Park, H. (Hojun), You, S.C. (Seng Chan), Park, R.W. (Rae Woong), Rijnbeek, P.R. (Peter), Van Zandt, M. (Mui), Reich, C. (Christian), Vashisht, R. (Rohit), Wu, Y. (Yonghui), Duke, J.D. (Jon D.), Hripcsak, G. (G.), Madigan, D. (David), Shah, N.H. (Nigam H.), Ryan, P.B. (Patrick), Schuemie, M.J. (Martijn), and Suchard, M.A. (Marc)

Abstract

Alendronate and raloxifene are among the most popular anti-osteoporosis medications. However, there is a lack of head-to-head comparative effectiveness studies comparing the two treatments. We conducted a retrospective large-scale multicenter study encompassing over 300 million patients across nine databases encoded in the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM). The primary outcome was the incidence of osteoporotic hip fracture, while secondary outcomes were vertebral fracture, atypical femoral fracture (AFF), osteonecrosis of the jaw (ONJ), and esophageal cancer. We used propensity score trimming and stratification based on an expansive propensity score model with all pre-treatment patient characteritistcs. We accounted for unmeasured confounding using negative control outcomes to estimate and adjust for residual systematic bias in each data source. We identified 283,586 alendronate patients and 40,463 raloxifene patients. There were 7.48 hip fracture, 8.18 vertebral fracture, 1.14 AFF, 0.21 esophageal cancer and 0.09 ONJ events per 1,000 person-years in the alendronate cohort and 6.62, 7.36, 0.69, 0.22 and 0.06 events per 1,000 person-years, respectively, in the raloxifene cohort. Alendronate and raloxifene have a similar hip fracture risk (hazard ratio [HR] 1.03, 95% confidence interval [CI] 0.94–1.13), but alendronate users are more likely to have vertebral fractures (HR 1.07, 95% CI 1.01–1.14). Alendronate has higher risk for AFF (HR 1.51, 95% CI 1.23–1.84) but similar risk for esophageal cancer (HR 0.95, 95% CI 0.53–1.70), and ONJ (HR 1.62, 95% CI 0.78–3.34). We demonstrated substantial control of measured confounding by propensity score adjustment, and minimal residual systematic bias through negative control experiments, lending credibility to our effect estimates. Raloxifene is as effective as alendronate and may remain an option in the prevention of osteoporotic fracture.

Published
2020
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3. Deep phenotyping of 34,128 patients hospitalised with COVID-19 and a comparison with 81,596 influenza patients in America, Europe and Asia: an international network study.

Author

Burn, E, You, SC, Sena, A, Kostka, K, Abedtash, H, Abrahao, MTF, Alberga, A, Alghoul, H, Alser, O, Alshammari, TM, Aragon, M, Areia, C, Banda, JM, Cho, J, Culhane, AC, Davydov, A, DeFalco, FJ, Duarte-Salles, T, DuVall, SL, Falconer, T, Fernandez-Bertolin, S, Gao, W, Golozar, A, Hardin, J, Hripcsak, G, Huser, V, Jeon, H, Jing, Y, Jung, CY, Kaas-Hansen, BS, Kaduk, D, Kent, S, Kim, Y, Kolovos, S, Lane, J, Lee, H, Lynch, KE, Makadia, R, Matheny, ME, Mehta, P, Morales, DR, Natarajan, K, Nyberg, F, Ostropolets, A, Park, RW, Park, J, Posada, JD, Prats-Uribe, A, Rao, GA, Reich, C, Rho, Y, Rijnbeek, P, Schilling, LM, Schuemie, M, Shah, NH, Shoaibi, A, Song, S, Spotnitz, M, Suchard, MA, Swerdel, J, Vizcaya, D, Volpe, S, Wen, H, Williams, AE, Yimer, BB, Zhang, L, Zhuk, O, Prieto-Alhambra, D, Ryan, P, Burn, E, You, SC, Sena, A, Kostka, K, Abedtash, H, Abrahao, MTF, Alberga, A, Alghoul, H, Alser, O, Alshammari, TM, Aragon, M, Areia, C, Banda, JM, Cho, J, Culhane, AC, Davydov, A, DeFalco, FJ, Duarte-Salles, T, DuVall, SL, Falconer, T, Fernandez-Bertolin, S, Gao, W, Golozar, A, Hardin, J, Hripcsak, G, Huser, V, Jeon, H, Jing, Y, Jung, CY, Kaas-Hansen, BS, Kaduk, D, Kent, S, Kim, Y, Kolovos, S, Lane, J, Lee, H, Lynch, KE, Makadia, R, Matheny, ME, Mehta, P, Morales, DR, Natarajan, K, Nyberg, F, Ostropolets, A, Park, RW, Park, J, Posada, JD, Prats-Uribe, A, Rao, GA, Reich, C, Rho, Y, Rijnbeek, P, Schilling, LM, Schuemie, M, Shah, NH, Shoaibi, A, Song, S, Spotnitz, M, Suchard, MA, Swerdel, J, Vizcaya, D, Volpe, S, Wen, H, Williams, AE, Yimer, BB, Zhang, L, Zhuk, O, Prieto-Alhambra, D, and Ryan, P

Abstract

Background In this study we phenotyped individuals hospitalised with coronavirus disease 2019 (COVID-19) in depth, summarising entire medical histories, including medications, as captured in routinely collected data drawn from databases across three continents. We then compared individuals hospitalised with COVID-19 to those previously hospitalised with influenza. Methods We report demographics, previously recorded conditions and medication use of patients hospitalised with COVID-19 in the US (Columbia University Irving Medical Center [CUIMC], Premier Healthcare Database [PHD], UCHealth System Health Data Compass Database [UC HDC], and the Department of Veterans Affairs [VA OMOP]), in South Korea (Health Insurance Review & Assessment [HIRA]), and Spain (The Information System for Research in Primary Care [SIDIAP] and HM Hospitales [HM]). These patients were then compared with patients hospitalised with influenza in 2014-19. Results 34,128 (US: 8,362, South Korea: 7,341, Spain: 18,425) individuals hospitalised with COVID-19 were included. Between 4,811 (HM) and 11,643 (CUIMC) unique aggregate characteristics were extracted per patient, with all summarised in an accompanying interactive website (http://evidence.ohdsi.org/Covid19CharacterizationHospitalization/). Patients were majority male in the US (CUIMC: 52%, PHD: 52%, UC HDC: 54%, VA OMOP: 94%,) and Spain (SIDIAP: 54%, HM: 60%), but were predominantly female in South Korea (HIRA: 60%). Age profiles varied across data sources. Prevalence of asthma ranged from 4% to 15%, diabetes from 13% to 43%, and hypertensive disorder from 24% to 70% across data sources. Between 14% and 33% were taking drugs acting on the renin-angiotensin system in the 30 days prior to hospitalisation. Compared to 81,596 individuals hospitalised with influenza in 2014-19, patients admitted with COVID-19 were more typically male, younger, and healthier, with fewer comorbidities and lower medication use. Conclusions We provide a detailed characte

Published
2020

4. Deep phenotyping of 34,128 adult patients hospitalised with COVID-19 in an international network study

Author

Burn, E, You, SC, Sena, AG, Kostka, K, Abedtash, H, Abrahao, MTF, Alberga, A, Alghoul, H, Alser, O, Alshammari, TM, Aragon, M, Areia, C, Banda, JM, Cho, J, Culhane, AC, Davydov, A, DeFalco, FJ, Duarte-Salles, T, DuVall, S, Falconer, T, Fernandez-Bertolin, S, Gao, W, Golozar, A, Hardin, J, Hripcsak, G, Huser, V, Jeon, H, Jing, Y, Jung, CY, Kaas-Hansen, BS, Kaduk, D, Kent, S, Kim, Y, Kolovos, S, Lane, JCE, Lee, H, Lynch, KE, Makadia, R, Matheny, ME, Mehta, PP, Morales, DR, Natarajan, K, Nyberg, F, Ostropolets, A, Park, RW, Park, J, Posada, JD, Prats-Uribe, A, Rao, G, Reich, C, Rho, Y, Rijnbeek, P, Schilling, LM, Schuemie, M, Shah, NH, Shoaibi, A, Song, S, Spotnitz, M, Suchard, MA, Swerdel, JN, Vizcaya, D, Volpe, S, Wen, H, Williams, AE, Yimer, BB, Zhang, L, Zhuk, O, Prieto-Alhambra, D, Ryan, P, Burn, E, You, SC, Sena, AG, Kostka, K, Abedtash, H, Abrahao, MTF, Alberga, A, Alghoul, H, Alser, O, Alshammari, TM, Aragon, M, Areia, C, Banda, JM, Cho, J, Culhane, AC, Davydov, A, DeFalco, FJ, Duarte-Salles, T, DuVall, S, Falconer, T, Fernandez-Bertolin, S, Gao, W, Golozar, A, Hardin, J, Hripcsak, G, Huser, V, Jeon, H, Jing, Y, Jung, CY, Kaas-Hansen, BS, Kaduk, D, Kent, S, Kim, Y, Kolovos, S, Lane, JCE, Lee, H, Lynch, KE, Makadia, R, Matheny, ME, Mehta, PP, Morales, DR, Natarajan, K, Nyberg, F, Ostropolets, A, Park, RW, Park, J, Posada, JD, Prats-Uribe, A, Rao, G, Reich, C, Rho, Y, Rijnbeek, P, Schilling, LM, Schuemie, M, Shah, NH, Shoaibi, A, Song, S, Spotnitz, M, Suchard, MA, Swerdel, JN, Vizcaya, D, Volpe, S, Wen, H, Williams, AE, Yimer, BB, Zhang, L, Zhuk, O, Prieto-Alhambra, D, and Ryan, P

Abstract

Comorbid conditions appear to be common among individuals hospitalised with coronavirus disease 2019 (COVID-19) but estimates of prevalence vary and little is known about the prior medication use of patients. Here, we describe the characteristics of adults hospitalised with COVID-19 and compare them with influenza patients. We include 34,128 (US: 8362, South Korea: 7341, Spain: 18,425) COVID-19 patients, summarising between 4811 and 11,643 unique aggregate characteristics. COVID-19 patients have been majority male in the US and Spain, but predominantly female in South Korea. Age profiles vary across data sources. Compared to 84,585 individuals hospitalised with influenza in 2014-19, COVID-19 patients have more typically been male, younger, and with fewer comorbidities and lower medication use. While protecting groups vulnerable to influenza is likely a useful starting point in the response to COVID-19, strategies will likely need to be broadened to reflect the particular characteristics of individuals being hospitalised with COVID-19.

Published
2020

5. Deep phenotyping of 34,128 adult patients hospitalised with COVID-19 in an international network study

Author

Burn, E, You, SC, Sena, Anthony, Kostka, K, Abedtash, H, Abrahao, MTF, Alberga, A, Alghoul, H, Alser, O, Alshammari, TM, Aragon, M, Areia, C, Banda, JM, Cho, J, Culhane, AC, Davydov, A, DeFalco, FJ, Duarte-Salles, T, DuVall, S, Falconer, T, Fernandez-Bertolin, S, Gao, WH, Golozar, A, Hardin, J, Hripcsak, G, Huser, V, Jeon, H, Jing, YH, Jung, CY, Kaas-Hansen, BS, Kaduk, D, Kent, S, Kim, Y, Kolovos, S, Lane, JCE, Lee, H, Lynch, KE, Makadia, R, Matheny, ME, Mehta, PP, Morales, DR, Natarajan, K, Nyberg, F, Ostropolets, A, Park, RW, Park, J (Judy), Posada, JD, Prats-Uribe, A, Rao, G, Reich, C, Rho, Y, Rijnbeek, Peter, Schilling, LM, Schuemie, Martijn, Shah, NH, Shoaibi, A, Song, S, Spotnitz, M, Suchard, MA, Swerdel, JN, Vizcaya, D, Volpe, S, Wen, HN, Williams, AE, Yimer, BB, Zhang, Lin, Zhuk, O, Prieto-Alhambra, D, Ryan, P, Burn, E, You, SC, Sena, Anthony, Kostka, K, Abedtash, H, Abrahao, MTF, Alberga, A, Alghoul, H, Alser, O, Alshammari, TM, Aragon, M, Areia, C, Banda, JM, Cho, J, Culhane, AC, Davydov, A, DeFalco, FJ, Duarte-Salles, T, DuVall, S, Falconer, T, Fernandez-Bertolin, S, Gao, WH, Golozar, A, Hardin, J, Hripcsak, G, Huser, V, Jeon, H, Jing, YH, Jung, CY, Kaas-Hansen, BS, Kaduk, D, Kent, S, Kim, Y, Kolovos, S, Lane, JCE, Lee, H, Lynch, KE, Makadia, R, Matheny, ME, Mehta, PP, Morales, DR, Natarajan, K, Nyberg, F, Ostropolets, A, Park, RW, Park, J (Judy), Posada, JD, Prats-Uribe, A, Rao, G, Reich, C, Rho, Y, Rijnbeek, Peter, Schilling, LM, Schuemie, Martijn, Shah, NH, Shoaibi, A, Song, S, Spotnitz, M, Suchard, MA, Swerdel, JN, Vizcaya, D, Volpe, S, Wen, HN, Williams, AE, Yimer, BB, Zhang, Lin, Zhuk, O, Prieto-Alhambra, D, and Ryan, P

Published
2020

6. Comparative safety and effectiveness of alendronate versus raloxifene in women with osteoporosis

Author

Kim, Y, Tian, YX, Yang, JX, Huser, V, Jin, P, Lambert, CG, Park, H, You, SC, Park, RW, Rijnbeek, Peter, Van Zandt, M, Reich, C, Vashisht, R, Wu, YH, Duke, J, Hripcsak, G, Madigan, D, Shah, NH, Ryan, PB, Schuemie, MJ, Suchard, MA, Kim, Y, Tian, YX, Yang, JX, Huser, V, Jin, P, Lambert, CG, Park, H, You, SC, Park, RW, Rijnbeek, Peter, Van Zandt, M, Reich, C, Vashisht, R, Wu, YH, Duke, J, Hripcsak, G, Madigan, D, Shah, NH, Ryan, PB, Schuemie, MJ, and Suchard, MA

Published
2020

7. Bridging Islands of Information to Establish an Integrated Knowledge Base of Drugs and Health Outcomes of Interest

Author

Boyce, C.S. (Christopher), Ryan, P.B. (Patrick), Norén, G.N. (G. Niklas), Schuemie, M.J. (Martijn), Reich, C. (Christian), Duke, J. (Jon), Tatonetti, N.P. (Nicholas), Trifirò, G. (Gianluca), Harpaz, R. (Rave), Overhage, J.M. (J. Marc), Hartzema, A.G. (Abraham), Khayter, M. (Mark), Voss, E.A. (Erica), Lambert, C.G. (Christophe), Huser, V. (Vojtech), Dumontier, J., Boyce, C.S. (Christopher), Ryan, P.B. (Patrick), Norén, G.N. (G. Niklas), Schuemie, M.J. (Martijn), Reich, C. (Christian), Duke, J. (Jon), Tatonetti, N.P. (Nicholas), Trifirò, G. (Gianluca), Harpaz, R. (Rave), Overhage, J.M. (J. Marc), Hartzema, A.G. (Abraham), Khayter, M. (Mark), Voss, E.A. (Erica), Lambert, C.G. (Christophe), Huser, V. (Vojtech), and Dumontier, J.

Abstract

The entire drug safety enterprise has a need to search, retrieve, evaluate, and synthesize scientific evidence more efficiently. This discovery and synthesis process would be greatly accelerated through access to a common framework that brings all relevant information sources together within a standardized structure. This presents an opportunity to establish an open-source community effort to develop a global knowledge base, one that brings together and standardizes all available information for all drugs and all health outcomes of interest (HOIs) from all electronic sources pertinent to drug safety. To make this vision a reality, we have established a workgroup within the Observational Health Data Sciences and Informatics (OHDSI, http://ohdsi.org) collaborative. The workgroup's mission is to develop an open-source standardized knowledge base for the effects of medical products and an efficient procedure for maintaining and expanding it. The knowledge base will make it simpler for practitioners to access, retrieve, and synthesize evidence so that they can reach a rigorous and accurate assessment of causal relationships between a given drug and HOI. Development of the knowledge base will proceed with the measureable goal of supporting an efficient and thorough evidence-based assessment of the effects of 1,000 active ingredients across 100 HOIs. This non-trivial task will result in a high-quality and generally applicable drug safety knowledge base. It will also yield a reference standard of drug-HOI pairs that will enable more advanced methodological research that empirically evaluates the performance of drug safety analysis methods.

Published
2014
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