Is Machine Learning a Better Way to Identify COVID-19 Patients Who Might Benefit from Hydroxychloroquine Treatment?—The IDENTIFY Trial
Hoyt Burdick, Carson Lam, Samson Mataraso, Anna Siefkas, Gregory Braden, R Phillip Dellinger, Andrea Mccoy, Jean-Louis Vincent, Abigail Green-Saxena, Gina Barnes, Jana Hoffman, Jacob Calvert, Emily Pellegrini, Ritankar Das
Journal of Clinical Medicine, doi:10.3390/jcm9123834
Therapeutic agents for the novel coronavirus disease 2019 (COVID-19) have been proposed, but evidence supporting their use is limited. A machine learning algorithm was developed in order to identify a subpopulation of COVID-19 patients for whom hydroxychloroquine was associated with improved survival; this population might be relevant for study in a clinical trial. A pragmatic trial was conducted at six United States hospitals. We enrolled COVID-19 patients that were admitted between 10 March and 4 June 2020. Treatment was not randomized. The study endpoint was mortality; discharge was a competing event. Hazard ratios were obtained on the entire population, and on the subpopulation indicated by the algorithm as suitable for treatment. A total of 290 patients were enrolled. In the subpopulation that was identified by the algorithm, hydroxychloroquine was associated with a statistically significant (p = 0.011) increase in survival (adjusted hazard ratio 0.29, 95% confidence interval (CI) 0.11-0.75). Adjusted survival among the algorithm indicated patients was 82.6% in the treated arm and 51.2% in the arm not treated. No association between treatment and mortality was observed in the general population. A 31% increase in survival at the end of the study was observed in a population of COVID-19 patients that were identified by a machine learning algorithm as having a better outcome with hydroxychloroquine treatment. Precision medicine approaches may be useful in identifying a subpopulation of COVID-19 patients more likely to be proven to benefit from hydroxychloroquine treatment in a clinical trial.
References
Aboughdir, Kirwin, Khader, Wang, Prognostic Value of Cardiovascular Biomarkers in COVID-19: A Review, Viruses,
doi:10.3390/v12050527Ahn, Shin, Kim, Lee, Kim et al., Current Status of Epidemiology, Diagnosis, Therapeutics, and Vaccines for Novel Coronavirus Disease
Arshad, Kilgore, Chaudhry, Jacobsen, Wang et al., Treatment with hydroxychloroquine, azithromycin, and combination in patients hospitalized with COVID, Int. J. Infect. Dis,
doi:10.1016/j.ijid.2020.06.099Ayerbe, Risco-Risco, Ayis, The association of treatment with hydroxychloroquine and hospital mortality in COVID-19 patients, Intern. Emerg. Med,
doi:10.1007/s11739-020-02505-xAzoulay, Fartoukh, Darmon, Géri, Voiriot et al., Increased mortality in patients with severe SARS-CoV-2 infection admitted within seven days of disease onset, Intensiv. Care Med,
doi:10.1007/s00134-020-06202-3Biot, Daher, Chavain, Fandeur, Khalife et al., Design and Synthesis of Hydroxyferroquine Derivatives with Antimalarial and Antiviral Activities, J. Med. Chem
Borba, Val, Sampaio, Alexandre, Melo et al., Effect of High vs Low Doses of Chloroquine Diphosphate as Adjunctive Therapy for Patients Hospitalized with Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Infection: A Randomized Clinical Trial, JAMA Netw. Open
Borba, Val, Sampaio, Alexandre, Melo et al., Effect of High vs Low Doses of Chloroquine References
Boulware, Pullen, Bangdiwala, Pastick, Lofgren et al., A Randomized Trial of Hydroxychloroquine as Postexposure Prophylaxis for Covid-19, New Engl. J. Med,
doi:10.1056/NEJMoa2016638Cao, Wang, Wen, Liu, Wang et al., A Trial of Lopinavir-Ritonavir in Adults Hospitalized with Severe Covid-19, New Engl. J. Med,
doi:10.1056/NEJMoa2001282Cao, Wang, Wen, Liu, Wang et al., A Trial of Lopinavir-Ritonavir in Adults Hospitalized with Severe Covid-19, New Engl. J. Med,
doi:10.1056/NEJMoa2001282Catteau, Dauby, Montourcy, Bottieau, Hautekiet et al., Low-dose hydroxychloroquine therapy and mortality in hospitalised patients with COVID-19: A nationwide observational study of 8075 participants, Int. J. Antimicrob. Agents,
doi:10.1016/j.ijantimicag.2020.106144Cavalcanti, Zampieri, Rosa, Azevedo, Veiga et al., Hydroxychloroquine with or without Azithromycin in Mild-to-Moderate Covid-19, N. Engl. J. Med,
doi:10.1056/NEJMoa2019014Cortegiani, Ingoglia, Ippolito, Giarratano, Einav, A systematic review on the efficacy and safety of chloroquine for the treatment of COVID-19, J. Crit. Care,
doi:10.1016/j.jcrc.2020.03.005Dauby, Bottieau, The unfinished story of hydroxychloroquine in COVID-19: The right anti-inflammatory dose at the right moment?, Int. J. Infect. Dis,
doi:10.1016/j.ijid.2020.10.032Devaux, Rolain, Colson, Raoult, New insights on the antiviral effects of chloroquine against coronavirus: What to expect for COVID-19?, Int. J. Antimicrob. Agents,
doi:10.1016/j.ijantimicag.2020.105938Devaux, Rolain, Colson, Raoult, New insights on the antiviral effects of chloroquine against coronavirus: What to expect for COVID-19?, Int. J. Antimicrob. Agents,
doi:10.1016/j.ijantimicag.2020.105938Di Castelnuovo, Costanzo, Antinori, Berselli, Blandi et al., Use of hydroxychloroquine in hospitalised COVID-19 patients is associated with reduced mortality: Findings from the observational multicentre Italian CORIST study, Eur. J. Intern. Med,
doi:10.1016/j.ejim.2020.08.019Gautret, Lagier, Parola, Hoang, Meddeb et al., Hydroxychloroquine and azithromycin as a treatment of COVID-19: Results of an open-label non-randomized clinical trial, Int. J. Antimicrob. Agents,
doi:10.1016/j.ijantimicag.2020.105949Geleris, Sun, Platt, Zucker, Baldwin et al., Observational Study of Hydroxychloroquine in Hospitalized Patients with Covid-19, N. Engl. J. Med,
doi:10.1056/NEJMoa2012410Gentry, Humphrey, Thind, Hendrickson, Kurdgelashvili et al., Long-term hydroxychloroquine use in patients with rheumatic conditions and development of SARS-CoV-2 infection: A retrospective cohort study, Lancet Rheumatol,
doi:10.1016/S2665-9913(20)30305-2Hernandez, Roman, Pasupuleti, Barboza-Meca, White, Update Alert 2: Hydroxychloroquine or Chloroquine for the Treatment or Prophylaxis of COVID, Ann. Intern. Med,
doi:10.7326/L20-1054Iyer, Hanrahan, Milowsky, Al-Ahmadie, Scott et al., Genome Sequencing Identifies a Basis for Everolimus Sensitivity, Science,
doi:10.1126/science.1226344Lai, Shih, Ko, Tang, Hsueh, Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and coronavirus disease-2019 (COVID-19): The epidemic and the challenges, Int. J. Antimicrob. Agents,
doi:10.1016/j.ijantimicag.2020.105924Lai, Shih, Ko, Tang, Hsueh, Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and coronavirus disease-2019 (COVID-19): The epidemic and the challenges, Int. J. Antimicrob. Agents,
doi:10.1016/j.ijantimicag.2020.105924Lammers, Brohet, Theunissen, Koster, Rood et al., Early hydroxychloroquine but not chloroquine use reduces ICU admission in COVID-19 patients, Int. J. Infect. Dis,
doi:10.1016/j.ijid.2020.09.1460Letai, Functional precision cancer medicine-Moving beyond pure genomics, Nat. Med,
doi:10.1038/nm.4389Mahévas, Tran, Roumier, Chabrol, Paule et al., Clinical efficacy of hydroxychloroquine in patients with covid-19 pneumonia who require oxygen: Observational comparative study using routine care data, BMJ,
doi:10.1136/bmj.m1844Menden, Iorio, Garnett, Mcdermott, Benes et al., Machine Learning Prediction of Cancer Cell Sensitivity to Drugs Based on Genomic and Chemical Properties, PLOS ONE,
doi:10.1371/journal.pone.0061318Molina, Delaugerre, Le Goff, Mela-Lima, Ponscarme et al., No evidence of rapid antiviral clearance or clinical benefit with the combination of hydroxychloroquine and azithromycin in patients with severe COVID-19 infection, Méd. Mal. Infect,
doi:10.1016/j.medmal.2020.03.006Pan, Peto, Karim, Alejandria, Henao-Restrepo et al., Repurposed antiviral drugs for COVID-19-Interim WHO SOLIDARITY trial results,
doi:10.1101/2020.10.15.20209817Richardson, Hirsch, Narasimhan, Crawford, Mcginn et al., Presenting Characteristics, Comorbidities, and Outcomes Among 5700 Patients Hospitalized With COVID-19 in the New York City Area, JAMA,
doi:10.1001/jama.2020.6775Rosenberg, Dufort, Udo, Wilberschied, Kumar et al., Association of Treatment With Hydroxychloroquine or Azithromycin With In-Hospital Mortality in Patients With COVID-19 in New York State, JAMA,
doi:10.1001/jama.2020.8630Sarma, Kaur, Kumar, Mahendru, Avti et al., Virological and clinical cure in COVID-19 patients treated with hydroxychloroquine: A systematic review and meta-analysis, J. Med Virol,
doi:10.1002/jmv.25898Schrezenmeier, Dörner, Mechanisms of action of hydroxychloroquine and chloroquine: Implications for rheumatology, Nat. Rev. Rheumatol,
doi:10.1038/s41584-020-0372-xSingh, Singh, Singh, Misra, Hydroxychloroquine in patients with COVID-19: A Systematic Review and meta-analysis, Diabetes Metab. Syndr. Clin. Res. Rev,
doi:10.1016/j.dsx.2020.05.017Skipper, Pastick, Engen, Bangdiwala, Abassi et al., Hydroxychloroquine in Nonhospitalized Adults With Early COVID, Ann. Intern. Med,
doi:10.7326/M20-4207Taccone, Gorham, Vincent, Hydroxychloroquine in the management of critically ill patients with COVID-19: The need for an evidence base, Lancet Respir. Med,
doi:10.1016/S2213-2600(20)30172-7Thémans, Belkhir, Dauby, Yombi, De Greef et al., Population Pharmacokinetics of Hydroxychloroquine in COVID-19 Patients: Implications for Dose Optimization, Eur. J. Drug Metab. Pharmacokinet,
doi:10.1007/s13318-020-00648-yVanderweele, Ding, Sensitivity Analysis in Observational Research: Introducing the E-Value, Ann. Intern. Med,
doi:10.7326/M16-2607Voss, Hakimi, Pham, Brannon, Chen et al., Tumor Genetic Analyses of Patients with Metastatic Renal Cell Carcinoma and Extended Benefit from mTOR Inhibitor Therapy, Clin. Cancer Res,
doi:10.1158/1078-0432.CCR-13-2345Wagle, Grabiner, Van Allen, Hodis, Jacobus et al., Activating mTOR Mutations in a Patient with an Extraordinary Response on a Phase I Trial of Everolimus and Pazopanib, Cancer Discov,
doi:10.1158/2159-8290.CD-13-0353Webb, Peltan, Jensen, Hoda, Hunter et al., Clinical criteria for COVID-19-associated hyperinflammatory syndrome: A cohort study, Lancet Rheumatol,
doi:10.1016/S2665-9913(20)30343-XYao, Ye, Zhang, Cui, Huang et al., In Vitro Antiviral Activity and Projection of Optimized Dosing Design of Hydroxychloroquine for the Treatment of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), Clin. Infect. Dis,
doi:10.1093/cid/ciaa237Yazdany, Kim, Use of Hydroxychloroquine and Chloroquine During the COVID-19 Pandemic: What Every Clinician Should Know, Ann. Intern. Med,
doi:10.7326/M20-1334{ 'indexed': {'date-parts': [[2024, 3, 7]], 'date-time': '2024-03-07T12:08:42Z', 'timestamp': 1709813322884},
'reference-count': 55,
'publisher': 'MDPI AG',
'issue': '12',
'license': [ { 'start': { 'date-parts': [[2020, 11, 26]],
'date-time': '2020-11-26T00:00:00Z',
'timestamp': 1606348800000},
'content-version': 'vor',
'delay-in-days': 0,
'URL': 'https://creativecommons.org/licenses/by/4.0/'}],
'content-domain': {'domain': [], 'crossmark-restriction': False},
'abstract': '<jats:p>Therapeutic agents for the novel coronavirus disease 2019 (COVID-19) have been '
'proposed, but evidence supporting their use is limited. A machine learning algorithm was '
'developed in order to identify a subpopulation of COVID-19 patients for whom '
'hydroxychloroquine was associated with improved survival; this population might be relevant '
'for study in a clinical trial. A pragmatic trial was conducted at six United States '
'hospitals. We enrolled COVID-19 patients that were admitted between 10 March and 4 June 2020. '
'Treatment was not randomized. The study endpoint was mortality; discharge was a competing '
'event. Hazard ratios were obtained on the entire population, and on the subpopulation '
'indicated by the algorithm as suitable for treatment. A total of 290 patients were enrolled. '
'In the subpopulation that was identified by the algorithm, hydroxychloroquine was associated '
'with a statistically significant (p = 0.011) increase in survival (adjusted hazard ratio '
'0.29, 95% confidence interval (CI) 0.11–0.75). Adjusted survival among the algorithm '
'indicated patients was 82.6% in the treated arm and 51.2% in the arm not treated. No '
'association between treatment and mortality was observed in the general population. A 31% '
'increase in survival at the end of the study was observed in a population of COVID-19 '
'patients that were identified by a machine learning algorithm as having a better outcome with '
'hydroxychloroquine treatment. Precision medicine approaches may be useful in identifying a '
'subpopulation of COVID-19 patients more likely to be proven to benefit from '
'hydroxychloroquine treatment in a clinical trial.</jats:p>',
'DOI': '10.3390/jcm9123834',
'type': 'journal-article',
'created': { 'date-parts': [[2020, 11, 27]],
'date-time': '2020-11-27T03:00:33Z',
'timestamp': 1606446033000},
'page': '3834',
'source': 'Crossref',
'is-referenced-by-count': 8,
'title': 'Is Machine Learning a Better Way to Identify COVID-19 Patients Who Might Benefit from '
'Hydroxychloroquine Treatment?—The IDENTIFY Trial',
'prefix': '10.3390',
'volume': '9',
'author': [ {'given': 'Hoyt', 'family': 'Burdick', 'sequence': 'first', 'affiliation': []},
{ 'ORCID': 'http://orcid.org/0000-0002-8255-4423',
'authenticated-orcid': False,
'given': 'Carson',
'family': 'Lam',
'sequence': 'additional',
'affiliation': []},
{ 'ORCID': 'http://orcid.org/0000-0003-3146-2243',
'authenticated-orcid': False,
'given': 'Samson',
'family': 'Mataraso',
'sequence': 'additional',
'affiliation': []},
{ 'ORCID': 'http://orcid.org/0000-0001-8379-6523',
'authenticated-orcid': False,
'given': 'Anna',
'family': 'Siefkas',
'sequence': 'additional',
'affiliation': []},
{'given': 'Gregory', 'family': 'Braden', 'sequence': 'additional', 'affiliation': []},
{'given': 'R. Phillip', 'family': 'Dellinger', 'sequence': 'additional', 'affiliation': []},
{'given': 'Andrea', 'family': 'McCoy', 'sequence': 'additional', 'affiliation': []},
{'given': 'Jean-Louis', 'family': 'Vincent', 'sequence': 'additional', 'affiliation': []},
{'given': 'Abigail', 'family': 'Green-Saxena', 'sequence': 'additional', 'affiliation': []},
{'given': 'Gina', 'family': 'Barnes', 'sequence': 'additional', 'affiliation': []},
{ 'ORCID': 'http://orcid.org/0000-0002-7745-3900',
'authenticated-orcid': False,
'given': 'Jana',
'family': 'Hoffman',
'sequence': 'additional',
'affiliation': []},
{'given': 'Jacob', 'family': 'Calvert', 'sequence': 'additional', 'affiliation': []},
{ 'ORCID': 'http://orcid.org/0000-0001-7614-9299',
'authenticated-orcid': False,
'given': 'Emily',
'family': 'Pellegrini',
'sequence': 'additional',
'affiliation': []},
{'given': 'Ritankar', 'family': 'Das', 'sequence': 'additional', 'affiliation': []}],
'member': '1968',
'published-online': {'date-parts': [[2020, 11, 26]]},
'reference': [ {'key': 'ref1', 'doi-asserted-by': 'publisher', 'DOI': '10.1016/j.ijantimicag.2020.105924'},
{'key': 'ref2', 'doi-asserted-by': 'publisher', 'DOI': '10.1016/j.ijantimicag.2020.105938'},
{'key': 'ref3', 'doi-asserted-by': 'publisher', 'DOI': '10.1056/NEJMoa2001282'},
{'key': 'ref4', 'doi-asserted-by': 'publisher', 'DOI': '10.1001/jamanetworkopen.2020.8857'},
{'key': 'ref5', 'doi-asserted-by': 'publisher', 'DOI': '10.1016/j.ijantimicag.2020.105949'},
{'key': 'ref6', 'doi-asserted-by': 'publisher', 'DOI': '10.1016/j.jcrc.2020.03.005'},
{'key': 'ref7', 'doi-asserted-by': 'publisher', 'DOI': '10.1056/NEJMoa2012410'},
{'key': 'ref8', 'doi-asserted-by': 'publisher', 'DOI': '10.1021/jm0601856'},
{'key': 'ref9', 'doi-asserted-by': 'publisher', 'DOI': '10.1093/cid/ciaa237'},
{'key': 'ref10', 'doi-asserted-by': 'publisher', 'DOI': '10.1016/j.medmal.2020.03.006'},
{'key': 'ref11', 'doi-asserted-by': 'publisher', 'DOI': '10.1101/2020.07.15.20151852'},
{'key': 'ref12', 'doi-asserted-by': 'publisher', 'DOI': '10.1002/jmv.25898'},
{'key': 'ref13', 'doi-asserted-by': 'publisher', 'DOI': '10.1016/j.dsx.2020.05.017'},
{'key': 'ref14', 'doi-asserted-by': 'publisher', 'DOI': '10.1007/s11739-020-02505-x'},
{'key': 'ref15', 'doi-asserted-by': 'publisher', 'DOI': '10.1016/j.ijid.2020.06.099'},
{'key': 'ref16', 'doi-asserted-by': 'publisher', 'DOI': '10.1016/j.ijantimicag.2020.106144'},
{'key': 'ref17', 'doi-asserted-by': 'publisher', 'DOI': '10.1016/j.ejim.2020.08.019'},
{'key': 'ref18', 'doi-asserted-by': 'publisher', 'DOI': '10.7326/M16-2607'},
{'key': 'ref19', 'doi-asserted-by': 'publisher', 'DOI': '10.1016/S2665-9913(20)30305-2'},
{'key': 'ref20', 'doi-asserted-by': 'publisher', 'DOI': '10.1001/jama.2020.8630'},
{'key': 'ref21', 'doi-asserted-by': 'publisher', 'DOI': '10.1007/s00134-020-06202-3'},
{'key': 'ref22', 'doi-asserted-by': 'publisher', 'DOI': '10.1007/s13318-020-00648-y'},
{'key': 'ref23', 'doi-asserted-by': 'publisher', 'DOI': '10.1056/NEJMp1500523'},
{'key': 'ref24', 'doi-asserted-by': 'publisher', 'DOI': '10.1038/nm.4389'},
{'key': 'ref25', 'doi-asserted-by': 'publisher', 'DOI': '10.1158/1078-0432.CCR-13-2345'},
{'key': 'ref26', 'doi-asserted-by': 'publisher', 'DOI': '10.1158/2159-8290.CD-13-0353'},
{'key': 'ref27', 'doi-asserted-by': 'publisher', 'DOI': '10.1126/science.1226344'},
{'key': 'ref28', 'doi-asserted-by': 'publisher', 'DOI': '10.1038/nature09339'},
{'key': 'ref29', 'doi-asserted-by': 'publisher', 'DOI': '10.1038/nature15816'},
{'key': 'ref30'},
{'key': 'ref31', 'doi-asserted-by': 'publisher', 'DOI': '10.1001/jama.290.12.1624'},
{'key': 'ref32', 'doi-asserted-by': 'publisher', 'DOI': '10.1080/01621459.1999.10474144'},
{'key': 'ref33', 'doi-asserted-by': 'publisher', 'DOI': '10.1016/S2213-2600(20)30172-7'},
{'key': 'ref34', 'doi-asserted-by': 'publisher', 'DOI': '10.1038/s41584-020-0372-x'},
{'key': 'ref35', 'doi-asserted-by': 'publisher', 'DOI': '10.1016/j.ijid.2020.10.032'},
{'key': 'ref36', 'doi-asserted-by': 'publisher', 'DOI': '10.1016/j.ijid.2020.09.1460'},
{'key': 'ref37'}, {'key': 'ref38'}, {'key': 'ref39'},
{'key': 'ref40', 'doi-asserted-by': 'publisher', 'DOI': '10.7326/L20-1054'},
{'key': 'ref41', 'doi-asserted-by': 'publisher', 'DOI': '10.7326/M20-4207'},
{'key': 'ref42', 'doi-asserted-by': 'publisher', 'DOI': '10.1056/NEJMoa2019014'},
{ 'key': 'ref43',
'unstructured': 'Global COVID-19 Prevention Trial of Hydroxychloroquine to '
'Resumehttp://www.medscape.com/viewarticle/933174.'},
{'key': 'ref44', 'doi-asserted-by': 'publisher', 'DOI': '10.1056/NEJMoa2016638'},
{'key': 'ref45', 'doi-asserted-by': 'publisher', 'DOI': '10.1101/2020.10.15.20209817'},
{'key': 'ref46', 'doi-asserted-by': 'publisher', 'DOI': '10.1136/bmj.m1432'},
{'key': 'ref47', 'doi-asserted-by': 'publisher', 'DOI': '10.1016/j.jaad.2020.04.031'},
{'key': 'ref48', 'doi-asserted-by': 'publisher', 'DOI': '10.7326/M20-1334'},
{'key': 'ref49', 'doi-asserted-by': 'publisher', 'DOI': '10.4014/jmb.2003.03011'},
{'key': 'ref50', 'doi-asserted-by': 'publisher', 'DOI': '10.1001/jama.2020.6775'},
{'key': 'ref51', 'doi-asserted-by': 'publisher', 'DOI': '10.3390/v12050527'},
{'key': 'ref52', 'doi-asserted-by': 'publisher', 'DOI': '10.1016/S2665-9913(20)30343-X'},
{'key': 'ref53', 'doi-asserted-by': 'publisher', 'DOI': '10.1136/bmj.m1844'},
{'key': 'ref54', 'doi-asserted-by': 'publisher', 'DOI': '10.1371/journal.pone.0061318'},
{'key': 'ref55', 'doi-asserted-by': 'publisher', 'DOI': '10.1002/sim.2655'}],
'container-title': 'Journal of Clinical Medicine',
'original-title': [],
'language': 'en',
'link': [ { 'URL': 'https://www.mdpi.com/2077-0383/9/12/3834/pdf',
'content-type': 'unspecified',
'content-version': 'vor',
'intended-application': 'similarity-checking'}],
'deposited': { 'date-parts': [[2020, 11, 27]],
'date-time': '2020-11-27T03:12:00Z',
'timestamp': 1606446720000},
'score': 1,
'resource': {'primary': {'URL': 'https://www.mdpi.com/2077-0383/9/12/3834'}},
'subtitle': [],
'short-title': [],
'issued': {'date-parts': [[2020, 11, 26]]},
'references-count': 55,
'journal-issue': {'issue': '12', 'published-online': {'date-parts': [[2020, 12]]}},
'alternative-id': ['jcm9123834'],
'URL': 'http://dx.doi.org/10.3390/jcm9123834',
'relation': {},
'ISSN': ['2077-0383'],
'subject': ['General Medicine'],
'container-title-short': 'JCM',
'published': {'date-parts': [[2020, 11, 26]]}}
