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Pharmacoepidemiology, Machine Learning and COVID-19: An intent-to-treat analysis of hydroxychloroquine, with or without azithromycin, and COVID-19 outcomes amongst hospitalized US Veterans

Gerlovin et al., American Journal of Epidemiology, doi:10.1093/aje/kwab183
Jun 2021  
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Mortality -22% Improvement Relative Risk Mortality (b) -21% Ventilation -55% Ventilation (b) -33% HCQ for COVID-19  Gerlovin et al.  LATE TREATMENT Is late treatment with HCQ beneficial for COVID-19? Retrospective 1,199 patients in the USA Higher ventilation with HCQ (p=0.02) c19hcq.org Gerlovin et al., American J. Epidemiol.., Jun 2021 FavorsHCQ Favorscontrol 0 0.5 1 1.5 2+
HCQ for COVID-19
1st treatment shown to reduce risk in March 2020
 
*, now with p < 0.00000000001 from 417 studies, recognized in 46 countries.
No treatment is 100% effective. Protocols combine treatments. * >10% efficacy, ≥3 studies.
4,800+ studies for 98 treatments. c19hcq.org
Retrospective 1,769 hospitalized patients in the USA showing no significant differences for HCQ, and higher intubation for HCQ+AZ.
risk of death, 22.0% higher, HR 1.22, p = 0.18, treatment 90 of 429 (21.0%), control 141 of 770 (18.3%), adjusted per study, HCQ+AZ.
risk of death, 21.0% higher, HR 1.21, p = 0.33, treatment 49 of 228 (21.5%), control 141 of 770 (18.3%), adjusted per study, HCQ.
risk of mechanical ventilation, 55.0% higher, HR 1.55, p = 0.02, treatment 64 of 429 (14.9%), control 69 of 770 (9.0%), adjusted per study, HCQ+AZ.
risk of mechanical ventilation, 33.0% higher, HR 1.33, p = 0.25, treatment 32 of 228 (14.0%), control 69 of 770 (9.0%), adjusted per study, HCQ.
Effect extraction follows pre-specified rules prioritizing more serious outcomes. Submit updates
Gerlovin et al., 24 Jun 2021, retrospective, USA, peer-reviewed, 21 authors.
This PaperHCQAll
Pharmacoepidemiology, Machine Learning, and COVID-19: An Intent-to-Treat Analysis of Hydroxychloroquine, With or Without Azithromycin, and COVID-19 Outcomes Among Hospitalized US Veterans
Dr Hanna Gerlovin, Daniel C Posner, Yuk-Lam Ho, Christopher T Rentsch, Janet P Tate, Joseph T King Jr, Katherine E Kurgansky, Ioana Danciu, Lauren Costa, Franciel A Linares, Ian D Goethert, Daniel A Jacobson, Matthew S Freiberg, Edmon Begoli, Sumitra Muralidhar, Rachel B Ramoni, Georgia Tourassi, J Michael Gaziano, Amy C Justice, David R Gagnon, Kelly Cho
American Journal of Epidemiology, doi:10.1093/aje/kwab183
Hydroxychloroquine (HCQ) was proposed as an early therapy for coronavirus disease 2019 (COVID-19) after in vitro studies indicated possible benefit. Previous in vivo observational studies have presented conf licting results, though recent randomized clinical trials have reported no benefit from HCQ among patients hospitalized with COVID-19. We examined the effects of HCQ alone and in combination with azithromycin in a hospitalized population of US veterans with COVID-19, using a propensity score-adjusted survival analysis with imputation of missing data. According to electronic health record data from the US Department of Veterans Affairs health care system, 64,055 US Veterans were tested for the virus that causes COVID-19 between March 1, 2020 and April 30, 2020. Of the 7,193 veterans who tested positive, 2,809 were hospitalized, and 657 individuals were prescribed HCQ within the first 48-hours of hospitalization for the treatment of COVID-19. There was no apparent benefit associated with HCQ receipt, alone or in combination with azithromycin, and there was an increased risk of intubation when HCQ was used in combination with azithromycin (hazard ratio = 1.55; 95% confidence interval: 1.07, 2.24). In conclusion, we assessed the effectiveness of HCQ with or without azithromycin in treatment of patients hospitalized with COVID-19, using a national sample of the US veteran population. Using rigorous study design and analytic methods to reduce confounding and bias, we found no evidence of a survival benefit from the administration of HCQ.
Hydroxychloroquine and Azithromycin for COVID-19 2417 Conflict of interest: none declared.
References
Alexander, Debono, Mammen, COVID-19 coronavirus research has overall low methodological quality thus far: case in point for chloroquine/hydroxychloroquine, J Clin Epidemiol
Andreani, Bideau, Duflot, In vitro testing of combined hydroxychloroquine and azithromycin on SARS-CoV-2 shows synergistic effect, Microb Pathog
Arshad, Kilgore, Chaudhry, Treatment with hydroxychloroquine, azithromycin, and combination in patients hospitalized with COVID-19, Int J Infect Dis
Austin, An introduction to propensity score methods for reducing the effects of confounding in observational studies, Multivariate Behav Res
Austin, Stuart, Moving towards best practice when using inverse probability of treatment weighting (IPTW) using the propensity score to estimate causal treatment effects in observational studies, Stat Med
Benson, Hartz, A comparison of observational studies and randomized, controlled trials, N Engl J Med
Bright, Re, Request for Emergency Use Authorization For Use of Chloroquine Phosphate or Hydroxychloroquine Sulfate Supplied From the Strategic National Stockpile for Treatment of
Bull-Otterson, Gray, Budnitz, Hydroxychloroquine and chloroquine prescribing patterns by provider specialty following initial reports of potential benefit for COVID-19 treatment -United States, January, MMWR Morb Mortal Wkly Rep
Chapman, Peterson, Turano, A natural language processing system for national COVID-19 surveillance in the US Department of Veterans Affairs
Core, R: A Language and Environment for Statistical Computing
Disbrow, Letter revoking emergency use authorization for chloroquine phosphate and hydroxychloroquine sulfate
Doove, Van Buuren, Dusseldorp, Recursive partitioning for missing data imputation in the presence of interaction effects, Comput Stat Data Anal
Fiolet, Guihur, Rebeaud, Effect of hydroxychloroquine with or without azithromycin on the mortality of coronavirus disease 2019 (COVID-19) patients: a systematic review and meta-analysis, Clin Microbiol Infect
Geleris, Sun, Platt, Observational study of hydroxychloroquine in hospitalized patients with Covid-19, N Engl J Med
Greenland, Lanes, Jara, Estimating effects from randomized trials with discontinuations: the need for intent-to-treat design and G-estimation, Clin Trials
Greenwell, Boehmke, Cunningham, Gbm: generalized boosted regression models
Greifer, Cobalt: covariate balance tables and plots
Greifer, WeightIt: weighting for covariate balance in observational studies
Hastie, Tibshirani, Friedman, Boosting and Additive Trees
Hernandez, Roman, Pasupuleti, Hydroxychloroquine or chloroquine for treatment or prophylaxis of COVID-19: a living systematic review, Ann Intern Med
Horby, Mafham, Effect of hydroxychloroquine in hospitalized patients with Covid-19, N Engl J Med
Kiley, NIH halts clinical trial of hydroxychloroquine
Kim, Sparks, Liew, A rush to judgment? Rapid reporting and dissemination of results and its consequences regarding the use of hydroxychloroquine for COVID-19, Ann Intern Med
Kupferschmidt, Cohen, Race to find COVID-19 treatments accelerates, Science
Lee, Lessler, Stuart, Improving propensity score weighting using machine learning, Stat Med
Lee, Mackenzie, Mcdonald, An observational cohort study of hydroxychloroquine and azithromycin for COVID-19: (can't get no) satisfaction, Int J Infect Dis
Magagnoli, Narendran, Pereira, Outcomes of hydroxychloroquine usage in United States veterans hospitalized with COVID-19, Med (
Mccaffrey, Griffin, Almirall, A tutorial on propensity score estimation for multiple treatments using generalized boosted models, Stat Med
Mccaffrey, Ridgeway, Morral, Propensity score estimation with boosted regression for evaluating causal effects in observational studies, Psychol Methods
Natekin, Knoll, Gradient boosting machines, a tutorial, Front Neurorobot
Nguyen, Collins, Spence, Comparison of the ability of double-robust estimators to correct bias in propensity score matching analysis. A Monte Carlo simulation study, Pharmacoepidemiol Drug Saf
Orkaby, Nussbaum, Ho, The burden of frailty among U.S. veterans and its association with mortality, 2002-2012, J Gerontol A Biol Sci Med Sci
Oscanoa, Romero-Ortuno, Carvajal, A pharmacological perspective of chloroquine in SARS-CoV-2 infection: an old drug for the fight against a new coronavirus?, Int J Antimicrob Agents
Pan, Peto, Karim, Repurposed antiviral drugs for COVID-19-interim WHO SOLIDARITY trial results, doi:10.1101/2020.10.15.20209817
Patil, Singhal, Masand, A systematic review on use of aminoquinolines for the therapeutic management of COVID-19: efficacy, safety and clinical trials, Life Sci
Pottegård, Kurz, Moore, Considerations for pharmacoepidemiological analyses in the SARS-CoV-2 pandemic, Pharmacoepidemiol Drug Saf
Rentsch, Kidwai-Khan, Tate, Patterns of COVID-19 testing and mortality by race and ethnicity among United States veterans: a nationwide cohort study, PLoS Med
Rivera, Peters, Panagiotou, Utilization of COVID-19 treatments and clinical outcomes among patients with cancer: a COVID-19 and Cancer Consortium (CCC19) cohort study, Cancer Discov
Rosenberg, Dufort, Udo, Association of treatment with hydroxychloroquine or azithromycin with in-hospital mortality in patients with COVID-19 in New York state, JAMA
Rubin, Schenker, Multiple imputation in health-care databases: an overview and some applications, Stat Med
Sbidian, Josse, Lemaitre, Hydroxychloroquine with or without azithromycin and in-hospital mortality or Hydroxychloroquine and Azithromycin for COVID-19
Schneeweiss, Rassen, Brown, Graphical depiction of longitudinal study designs in health care databases, Ann Intern Med
Self, Semler, Leither, Effect of hydroxychloroquine on clinical status at 14 days in hospitalized patients with COVID-19: a randomized clinical trial, JAMA
Setodji, Mccaffrey, Burgette, The right tool for the job: choosing between covariate-balancing and generalized boosted model propensity scores, Epidemiology
Singh, Singh, Singh, Hydroxychloroquine in patients with COVID-19: a systematic review and meta-analysis, Diabetes Metab Syndr
Sohn, Arnold, Maynard, Accuracy and completeness of mortality data in the Department of Veterans Affairs, Popul Health Metr
Spencer, Heneghan, Chronological bias
Tarek, Savarino, Pharmacokinetic basis of the hydroxychloroquine response in COVID-19: implications for therapy and prevention, Eur J Drug Metab Pharmacokinet
Therneau, Survival: a package for survival analysis in S. (R package version 3.2-3
Van Buuren, Groothuis-Oudshoorn, Mice: multivariate imputation by chained equations
Westreich, Lessler, Funk, Propensity score estimation: machine learning and classification methods as alternatives to logistic regression, J Clin Epidemiol
Yang, Webster-Clark, Lund, Propensity score methods to control for confounding in observational cohort studies: a statistical primer and application to endoscopy research, Gastrointest Endosc
Zhai, Lye, Kesselheim, Need for transparency and reliable evidence in emergency use authorizations for coronavirus disease 2019 (COVID-19) therapies, JAMA Intern Med
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'crossref', 'first-page': '399', 'DOI': '10.1080/00273171.2011.568786', 'article-title': 'An introduction to propensity score methods for reducing the effects of ' 'confounding in observational studies', 'volume': '46', 'author': 'Austin', 'year': '2011', 'journal-title': 'Multivariate Behav Res'}, { 'issue': '3', 'key': '2021110206552741700_ref25', 'doi-asserted-by': 'crossref', 'first-page': '337', 'DOI': '10.1002/sim.3782', 'article-title': 'Improving propensity score weighting using machine learning', 'volume': '29', 'author': 'Lee', 'year': '2010', 'journal-title': 'Stat Med'}, { 'issue': '4', 'key': '2021110206552741700_ref26', 'doi-asserted-by': 'crossref', 'first-page': '403', 'DOI': '10.1037/1082-989X.9.4.403', 'article-title': 'Propensity score estimation with boosted regression for evaluating ' 'causal effects in observational studies', 'volume': '9', 'author': 'McCaffrey', 'year': '2004', 'journal-title': 'Psychol Methods'}, { 'issue': '6', 'key': '2021110206552741700_ref27', 'doi-asserted-by': 'crossref', 'first-page': '802', 'DOI': '10.1097/EDE.0000000000000734', 'article-title': 'The right tool for the job: choosing between covariate-balancing and ' 'generalized boosted model propensity scores', 'volume': '28', 'author': 'Setodji', 'year': '2017', 'journal-title': 'Epidemiology'}, { 'issue': '3', 'key': '2021110206552741700_ref28', 'doi-asserted-by': 'crossref', 'first-page': '360', 'DOI': '10.1016/j.gie.2019.04.236', 'article-title': 'Propensity score methods to control for confounding in observational ' 'cohort studies: a statistical primer and application to endoscopy ' 'research', 'volume': '90', 'author': 'Yang', 'year': '2019', 'journal-title': 'Gastrointest Endosc'}, { 'issue': '8', 'key': '2021110206552741700_ref29', 'doi-asserted-by': 'crossref', 'first-page': '826', 'DOI': '10.1016/j.jclinepi.2009.11.020', 'article-title': 'Propensity score estimation: machine learning and classification ' 'methods as alternatives to logistic regression', 'volume': '63', 'author': 'Westreich', 'year': '2011', 'journal-title': 'J Clin Epidemiol'}, { 'issue': '6', 'key': '2021110206552741700_ref30', 'doi-asserted-by': 'crossref', 'first-page': '398', 'DOI': '10.7326/M18-3079', 'article-title': 'Graphical depiction of longitudinal study designs in health care ' 'databases', 'volume': '170', 'author': 'Schneeweiss', 'year': '2019', 'journal-title': 'Ann Intern Med'}, { 'key': '2021110206552741700_ref31', 'article-title': 'A natural language processing system for national COVID-19 surveillance ' 'in the US Department of Veterans Affairs', 'author': 'Chapman', 'year': '2020'}, { 'issue': '1', 'key': '2021110206552741700_ref32', 'doi-asserted-by': 'crossref', 'first-page': '2', 'DOI': '10.1186/1478-7954-4-2', 'article-title': 'Accuracy and completeness of mortality data in the Department of ' 'Veterans Affairs', 'volume': '4', 'author': 'Sohn', 'year': '2006', 'journal-title': 'Popul Health Metr'}, { 'issue': '8', 'key': '2021110206552741700_ref33', 'doi-asserted-by': 'crossref', 'first-page': '1257', 'DOI': '10.1093/gerona/gly232', 'article-title': 'The burden of frailty among U.S. veterans and its association with ' 'mortality, 2002–2012', 'volume': '74', 'author': 'Orkaby', 'year': '2019', 'journal-title': 'J Gerontol A Biol Sci Med Sci'}, { 'key': '2021110206552741700_ref34', 'volume-title': 'R: A Language and Environment for Statistical Computing, release 3.6.1', 'author': 'R Core Team', 'year': '2019'}, { 'key': '2021110206552741700_ref35', 'doi-asserted-by': 'crossref', 'first-page': '92', 'DOI': '10.1016/j.csda.2013.10.025', 'article-title': 'Recursive partitioning for missing data imputation in the presence of ' 'interaction effects', 'volume': '72', 'author': 'Doove', 'year': '2014', 'journal-title': 'Comput Stat Data Anal'}, { 'key': '2021110206552741700_ref36', 'doi-asserted-by': 'crossref', 'article-title': 'Mice: multivariate imputation by chained equations', 'author': 'Buuren', 'DOI': '10.18637/jss.v045.i03'}, { 'issue': '4', 'key': '2021110206552741700_ref37', 'doi-asserted-by': 'crossref', 'first-page': '585', 'DOI': '10.1002/sim.4780100410', 'article-title': 'Multiple imputation in health-care databases: an overview and some ' 'applications', 'volume': '10', 'author': 'Rubin', 'year': '1991', 'journal-title': 'Stat Med'}, { 'key': '2021110206552741700_ref38', 'first-page': '1', 'volume-title': 'In: The Elements of Statistical Learning. Springer Series in Statistics', 'author': 'Hastie', 'year': '2009'}, { 'key': '2021110206552741700_ref39', 'article-title': 'Gbm: generalized boosted regression models', 'author': 'Greenwell'}, { 'key': '2021110206552741700_ref40', 'article-title': 'WeightIt: weighting for covariate balance in observational studies', 'author': 'Greifer'}, { 'key': '2021110206552741700_ref41', 'article-title': 'Cobalt: covariate balance tables and plots', 'author': 'Greifer'}, { 'issue': 'Dec', 'key': '2021110206552741700_ref42', 'first-page': '21', 'article-title': 'Gradient boosting machines, a tutorial', 'volume': '7', 'author': 'Natekin', 'year': '2013', 'journal-title': 'Front Neurorobot'}, { 'key': '2021110206552741700_ref43', 'article-title': 'Survival: a package for survival analysis in S', 'author': 'Therneau'}, { 'issue': '19', 'key': '2021110206552741700_ref44', 'doi-asserted-by': 'crossref', 'first-page': '3388', 'DOI': '10.1002/sim.5753', 'article-title': 'A tutorial on propensity score estimation for multiple treatments using ' 'generalized boosted models', 'volume': '32', 'author': 'McCaffrey', 'year': '2013', 'journal-title': 'Stat Med'}, { 'issue': '12', 'key': '2021110206552741700_ref45', 'doi-asserted-by': 'crossref', 'first-page': '1513', 'DOI': '10.1002/pds.4325', 'article-title': 'Comparison of the ability of double-robust estimators to correct bias ' 'in propensity score matching analysis. A Monte Carlo simulation study', 'volume': '26', 'author': 'Nguyen', 'year': '2017', 'journal-title': 'Pharmacoepidemiol Drug Saf.'}, {'key': '2021110206552741700_ref46'}, { 'issue': '28', 'key': '2021110206552741700_ref47', 'doi-asserted-by': 'crossref', 'first-page': '3661', 'DOI': '10.1002/sim.6607', 'article-title': 'Moving towards best practice when using inverse probability of ' 'treatment weighting (IPTW) using the propensity score to estimate ' 'causal treatment effects in observational studies', 'volume': '34', 'author': 'Austin', 'year': '2015', 'journal-title': 'Stat Med'}, { 'issue': '24', 'key': '2021110206552741700_ref48', 'doi-asserted-by': 'crossref', 'first-page': '2493', 'DOI': '10.1001/jama.2020.8630', 'article-title': 'Association of treatment with hydroxychloroquine or azithromycin with ' 'in-hospital mortality in patients with COVID-19 in New York state', 'volume': '323', 'author': 'Rosenberg', 'year': '2020', 'journal-title': 'JAMA'}, { 'issue': '10', 'key': '2021110206552741700_ref49', 'doi-asserted-by': 'crossref', 'first-page': '1514', 'DOI': '10.1158/2159-8290.CD-20-0941', 'article-title': 'Utilization of COVID-19 treatments and clinical outcomes among patients ' 'with cancer: a COVID-19 and Cancer Consortium (CCC19) cohort study', 'volume': '10', 'author': 'Rivera', 'year': '2020', 'journal-title': 'Cancer Discov'}, { 'key': '2021110206552741700_ref50', 'doi-asserted-by': 'crossref', 'article-title': 'Hydroxychloroquine with or without azithromycin and in-hospital ' 'mortality or discharge in patients hospitalized for COVID-19 infection: ' 'a cohort study of 4,642 in-patients in France', 'author': 'Sbidian', 'year': '2020', 'DOI': '10.1101/2020.06.16.20132597'}, { 'issue': '0', 'key': '2021110206552741700_ref51', 'doi-asserted-by': 'crossref', 'first-page': '396', 'DOI': '10.1016/j.ijid.2020.06.099', 'article-title': 'Treatment with hydroxychloroquine, azithromycin, and combination in ' 'patients hospitalized with COVID-19', 'volume': '97', 'author': 'Arshad', 'year': '2020', 'journal-title': 'Int J Infect Dis'}, { 'key': '2021110206552741700_ref52', 'doi-asserted-by': 'crossref', 'first-page': '216', 'DOI': '10.1016/j.ijid.2020.06.095', 'article-title': 'An observational cohort study of hydroxychloroquine and azithromycin ' "for COVID-19: (can't get no) satisfaction", 'volume': '98', 'author': 'Lee', 'year': '2020', 'journal-title': 'Int J Infect Dis'}, {'key': '2021110206552741700_ref53', 'volume-title': 'Catalogue of Bias 2017', 'author': ''}, { 'issue': '35', 'key': '2021110206552741700_ref54', 'doi-asserted-by': 'crossref', 'first-page': '1210', 'DOI': '10.15585/mmwr.mm6935a4', 'article-title': 'Hydroxychloroquine and chloroquine prescribing patterns by provider ' 'specialty following initial reports of potential benefit for COVID-19 ' 'treatment - United States, January-June 2020', 'volume': '69', 'author': 'Bull-Otterson', 'year': '2020', 'journal-title': 'MMWR Morb Mortal Wkly Rep'}, { 'issue': '9', 'key': '2021110206552741700_ref55', 'doi-asserted-by': 'crossref', 'DOI': '10.1371/journal.pmed.1003379', 'article-title': 'Patterns of COVID-19 testing and mortality by race and ethnicity among ' 'United States veterans: a nationwide cohort study', 'volume': '17', 'author': 'Rentsch', 'year': '2020', 'journal-title': 'PLoS Med'}, { 'issue': '25', 'key': '2021110206552741700_ref56', 'doi-asserted-by': 'crossref', 'first-page': '2411', 'DOI': '10.1056/NEJMoa2012410', 'article-title': 'Observational study of hydroxychloroquine in hospitalized patients with ' 'Covid-19', 'volume': '382', 'author': 'Geleris', 'year': '2020', 'journal-title': 'N Engl J Med'}, { 'issue': '1', 'key': '2021110206552741700_ref57', 'doi-asserted-by': 'crossref', 'first-page': '5', 'DOI': '10.1177/1740774507087703', 'article-title': 'Estimating effects from randomized trials with discontinuations: the ' 'need for intent-to-treat design and G-estimation', 'volume': '5', 'author': 'Greenland', 'year': '2008', 'journal-title': 'Clin Trials'}], 'container-title': 'American Journal of Epidemiology', 'original-title': [], 'language': 'en', 'link': [ { 'URL': 'http://academic.oup.com/aje/advance-article-pdf/doi/10.1093/aje/kwab183/40436006/kwab183.pdf', 'content-type': 'application/pdf', 'content-version': 'am', 'intended-application': 'syndication'}, { 'URL': 'http://academic.oup.com/aje/article-pdf/190/11/2405/41025403/kwab183.pdf', 'content-type': 'application/pdf', 'content-version': 'vor', 'intended-application': 'syndication'}, { 'URL': 'http://academic.oup.com/aje/article-pdf/190/11/2405/41025403/kwab183.pdf', 'content-type': 'unspecified', 'content-version': 'vor', 'intended-application': 'similarity-checking'}], 'deposited': { 'date-parts': [[2021, 11, 2]], 'date-time': '2021-11-02T06:56:36Z', 'timestamp': 1635836196000}, 'score': 1, 'resource': {'primary': {'URL': 'https://academic.oup.com/aje/article/190/11/2405/6308675'}}, 'subtitle': [], 'short-title': [], 'issued': {'date-parts': [[2021, 6, 24]]}, 'references-count': 57, 'journal-issue': { 'issue': '11', 'published-online': {'date-parts': [[2021, 6, 24]]}, 'published-print': {'date-parts': [[2021, 11, 2]]}}, 'URL': 'http://dx.doi.org/10.1093/aje/kwab183', 'relation': {}, 'ISSN': ['0002-9262', '1476-6256'], 'subject': ['Epidemiology'], 'published-other': {'date-parts': [[2021, 11]]}, 'published': {'date-parts': [[2021, 6, 24]]}}
Late treatment
is less effective
Please send us corrections, updates, or comments. c19early involves the extraction of 100,000+ datapoints from thousands of papers. Community updates help ensure high accuracy. Treatments and other interventions are complementary. All practical, effective, and safe means should be used based on risk/benefit analysis. No treatment or intervention is 100% available and effective for all current and future variants. We do not provide medical advice. Before taking any medication, consult a qualified physician who can provide personalized advice and details of risks and benefits based on your medical history and situation. FLCCC and WCH provide treatment protocols.
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