Evaluating the impact of policies recommending PrEP to subpopulations of men and transgender women who have sex with men based on demographic and behavioral risk factors
Autoři:
Holly Janes aff001; Marshall D. Brown aff001; David V. Glidden aff002; Kenneth H. Mayer aff003; Susan P. Buchbinder aff004; Vanessa M. McMahan aff005; Mauro Schechter aff006; Juan Guanira aff007; Martin Casapia aff008
Působiště autorů:
Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
aff001; Department of Epidemiology and Biostatistics, University of California School of Medicine, San Francisco, California, United States of America
aff002; Division of Infectious Diseases, Beth Israel Deaconess Medical Center, and The Fenway Institute, Fenway Health, Boston, Massachusetts, United States of America
aff003; Bridge HIV, San Francisco Department of Public Health, San Francisco, California, United States of America
aff004; Department of Medicine, University of Washington, Seattle, Washington, United States of America
aff005; Projeto Praça Onze, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil
aff006; Asociación Civil Impacta Salud y Educación, Lima, Peru
aff007; Asociación Civil Selva Amazónica, Iquitos, Peru
aff008
Vyšlo v časopise:
PLoS ONE 14(9)
Kategorie:
Research Article
prolekare.web.journal.doi_sk:
https://doi.org/10.1371/journal.pone.0222183
Souhrn
Introduction
Developing guidelines to inform the use of antiretroviral pre-exposure prophylaxis (PrEP) for HIV prevention in resource-limited settings must necessarily be informed by considering the resources and infrastructure needed for PrEP delivery. We describe an approach that identifies subpopulations of cisgender men who have sex with men (MSM) and transgender women (TGW) to prioritize for the rollout of PrEP in resource-limited settings.
Methods
We use data from the iPrEx study, a multi-national phase III study of PrEP for HIV prevention in MSM/TGW, to build statistical models that identify subpopulations at high risk of HIV acquisition without PrEP, and with high expected PrEP benefit. We then evaluate empirically the population impact of policies recommending PrEP to these subpopulations, and contrast these with existing policies.
Results
A policy recommending PrEP to a high risk subpopulation of MSM/TGW reporting condomless receptive anal intercourse over the last 3 months (estimated 3.3% 1-year HIV incidence) yields an estimated 1.95% absolute reduction in 1-year HIV incidence at the population level, and 3.83% reduction over 2 years. Importantly, such a policy requires rolling PrEP out to just 59.7% of MSM/TGW in the iPrEx population. We find that this policy is identical to that which prioritizes MSM/TGW with high expected PrEP benefit. It is estimated to achieve nearly the same reduction in HIV incidence as the PrEP guideline put forth by the US Centers for Disease Control, which relies on the measurement of more behavioral risk factors and which would recommend PrEP to a larger subset of the MSM/TGW population (86% vs. 60%).
Conclusions
These findings may be used to focus future mathematical modelling studies of PrEP in resource-limited settings on prioritizing PrEP for high-risk subpopulations of MSM/TGW. The statistical approach we took could be employed to develop PrEP policies for other at-risk populations and resource-limited settings.
Klíčová slova:
Biology and life sciences – Organisms – People and places – Population groupings – Medicine and health sciences – Microbiology – Medical microbiology – Microbial pathogens – Pathology and laboratory medicine – Pathogens – Infectious diseases – Viral pathogens – Immunodeficiency viruses – HIV – Retroviruses – Lentivirus – Viruses – RNA viruses – Public and occupational health – Preventive medicine – Viral diseases – HIV infections – Sexually transmitted diseases – Epidemiology – Medical risk factors – Sexuality groupings – Men who have sex with men – HIV epidemiology – Prophylaxis – Pre-exposure prophylaxis – HIV prevention
Zdroje
1. Grant RM, Lama JR, Anderson PL, McMahan V, Liu AY, Vargas L, et al. Preexposure chemoprophylaxis for HIV prevention in men who have sex with men. New England Journal of Medicine. 2010;363(27):2587–99. doi: 10.1056/NEJMoa1011205 21091279
2. Baeten JM, Donnell D, Ndase P, Mugo NR, Campbell JD, Wangisi J, et al. Antiretroviral prophylaxis for HIV prevention in heterosexual men and women. N Engl J Med. 2012;367(5):399–410. doi: 10.1056/NEJMoa1108524 22784037
3. Thigpen MC, Kebaabetswe PM, Paxton LA, Smith DK, Rose CE, Segolodi TM, et al. Antiretroviral preexposure prophylaxis for heterosexual HIV transmission in Botswana. N Engl J Med. 2012;367(5):423–34. doi: 10.1056/NEJMoa1110711 22784038
4. Molina J, Capitant C, Charreau I, Meyer L, Spire B, Pialoux G, et al. On demand PrEP with oral TDF-FTC in MSM: Results of the ANRS Ipergay trial. CROI, Seattle, WA. 2015;Abstract 23LB.
5. McCormack S, Dunn DT, Desai M, Dolling DI, Gafos M, Gilson R, et al. Pre-exposure prophylaxis to prevent the acquisition of HIV-1 infection (PROUD): effectiveness results from the pilot phase of a pragmatic open-label randomised trial. Lancet. 2016;387(10013):53–60. doi: 10.1016/S0140-6736(15)00056-2 26364263
6. Van Damme L, Corneli A, Ahmed K, Agot K, Lombaard J, Kapiga S, et al. Preexposure prophylaxis for HIV infection among African women. N Engl J Med. 2012;367(5):411–22. doi: 10.1056/NEJMoa1202614 22784040
7. Marrazzo JM, Ramjee G, Richardson BA, Gomez K, Mgodi N, Nair G, et al. Tenofovir-based preexposure prophylaxis for HIV infection among African women. N Engl J Med. 2015;372(6):509–18. doi: 10.1056/NEJMoa1402269 25651245
8. Kashuba AD, Patterson KB, Dumond JB, Cohen MS. Pre-exposure prophylaxis for HIV prevention: how to predict success. Lancet. 2012;379(9835):2409–11. doi: 10.1016/S0140-6736(11)61852-7 22153566
9. van der Straten A, Van Damme L, Haberer JE, Bangsberg DR. Unraveling the divergent results of pre-exposure prophylaxis trials for HIV prevention. AIDS. 2012;26(7):F13–9. doi: 10.1097/QAD.0b013e3283522272 22333749
10. Haberer JE, Baeten JM, Campbell J, Wangisi J, Katabira E, Ronald A, et al. Adherence to antiretroviral prophylaxis for HIV prevention: a substudy cohort within a clinical trial of serodiscordant couples in East Africa. PLoS Med. 2013;10(9):e1001511. doi: 10.1371/journal.pmed.1001511 24058300
11. Burgener A, Klatt N. Uncovering the role of the vaginal microbome in undermining PrEP efficacy in women. 21st International AIDS Conference; July 18–22, 2016; Durban, South Africa2016.
12. Williams BL, Lipkin I. Role of vaginal microciota in genital inflammation and enhancing HIV acquisition in women. 21st International AIDS Conference; July 18–21, 2016; Durban, South Africa2016.
13. Naranbhai V, Abdool Karim SS, Altfeld M, Samsunder N, Durgiah R, Sibeko S, et al. Innate immune activation enhances hiv acquisition in women, diminishing the effectiveness of tenofovir microbicide gel. J Infect Dis. 2012;206(7):993–1001. doi: 10.1093/infdis/jis465 22829639
14. Thomson KA, Baeten JM, Mugo NR, Bekker LG, Celum CL, Heffron R. Tenofovir-based oral preexposure prophylaxis prevents HIV infection among women. Curr Opin HIV AIDS. 2016;11(1):18–26. doi: 10.1097/COH.0000000000000207 26417954
15. Klatt NR, Cheu R, Birse K, Zevin AS, Perner M, Noel-Romas L, et al. Vaginal bacteria modify HIV tenofovir microbicide efficacy in African women. Science 2017;356:938–45. doi: 10.1126/science.aai9383 28572388
16. Patterson KB, Prince HA, Kraft E, Jenkins AJ, Shaheen NJ, Rooney JF, et al. Penetration of tenofovir and emtricitabine in mucosal tissues: implications for prevention of HIV-1 transmission. Sci Transl Med. 2011;3(112):112re4. doi: 10.1126/scitranslmed.3003174 22158861
17. Garrett KL, Cottrell ML, Prince HM, Sykes C, Schauer A, Peery A, et al. Concentrations of TFV and TFVdp in Female Mucosal Tissues After a Single Dose of TAF. CROI 2016; Feb 22–25; Boston2016.
18. Janes H, Corey L, Ramjee G, Carpp LN, Lombard C, Cohen MS, et al. Weighing the Evidence of Efficacy of Oral PrEP for HIV Prevention in Women in Southern Africa. AIDS Res Hum Retroviruses. 2018;34(8):645–56. doi: 10.1089/AID.2018.0031 29732896
19. endinghiv.org.au. Truvada Licensed for PrEP: ACON; 2016 [updated May 10]. Available from: http://endinghiv.org.au/nsw/truvada-licensed-for-prep/.
20. Dorresteijn JAN, Visseren FLJ, Ridker PM, Wassink AMJ, Steyerberg EW, van der Graaf Y, et al. Estimating treatment effects for individual patients based on the results of randomised clinical trials. British Medical Journal. 2011;343:1–13.
21. Kovalchik SA, Tammemagi M, DBerg CD, Caporaso NE, Riley TL, Korch M, et al. Targeting of low-dose CT screening according to the risk of lung-cancer death. New England Journal of Medicine. 2013;369:245–54. doi: 10.1056/NEJMoa1301851 23863051
22. Benchikh A, Savage C, Cronin A, Salama G, Villers A, Lilja H, et al. A panel of kallikrein markers can predict outcome of prostate biopsy following clinical work-up: an independent validation study from the European Randomized Study of Prostate Cancer screening, France. BMC Cancer. 2010;10:635. doi: 10.1186/1471-2407-10-635 21092177
23. Den RB, Yousefi K, Trabulsi EJ, Abdollah F, Choeurng V, Feng FY, et al. Genomic classifier identifies men with adverse pathology after radical prostatectomy who benefit from adjuvant radiation therapy. J Clin Oncol. 2015;33(8):944–51. doi: 10.1200/JCO.2014.59.0026 25667284
24. Thanassoulis G, Williams K, Altobelli KK, Pencina MJ, Cannon CP, Sniderman AD. Individualized Statin Benefit for Determining Statin Eligibility in the Primary Prevention of Cardiovascular Disease. Circulation. 2016;133(16):1574–81. doi: 10.1161/CIRCULATIONAHA.115.018383 26945047
25. Pletcher MJ, Pignone M, Jarmul JA, Moran AE, Vittinghoff E, Newman T. Population Impact & Efficiency of Benefit-Targeted Versus Risk-Targeted Statin Prescribing for Primary Prevention of Cardiovascular Disease. J Am Heart Assoc. 2017;6(2).
26. Pauker SG, Kassirer JP. Clinical Application of Decision-Analysis—Detailed Illustration. Semin Nucl Med. 1978;8(4):324–35. 754287
27. Vickers AJ, Elkin EB. Decision curve analysis: A novel method for evaluating prediction models. Med Decis Making. 2006;26(6):565–74. doi: 10.1177/0272989X06295361 17099194
28. Janes H, Pepe MS, Huang Y. A framework for evaluating markers used to select patient treatment. Med Decis Making. 2014;34(2):159–67. doi: 10.1177/0272989X13493147 23811760
29. Vickers AJ, Kattan MW, Daniel S. Method for evaluating prediction models that apply the results of randomized trials to individual patients. Trials. 2007;8.
30. Pauker SG, Kassirer JP. Therapeutic Decision-Making—Cost-Benefit Analysis. New England Journal of Medicine. 1975;293(5):229–34. doi: 10.1056/NEJM197507312930505 1143303
31. Hunink MM, Weinstein MC, Wittenberg E, Drummond MF, Pliskin JS, Wong JB, et al. Decision making in health and medicine: integrating evidence and valuesCambridge University Press; 2014.
32. Kerr KF, Brown MD, Zhu K, Janes H. Assessing the Clinical Impact of Risk Prediction Models With Decision Curves: Guidance for Correct Interpretation and Appropriate Use. J Clin Oncol. 2016;34(21):2534–40. doi: 10.1200/JCO.2015.65.5654 27247223
33. US Public Health Service. Preexposure prophylaxis for the prevention of HIV infection in the United States: A Clinical Practice Guideline. 2014.
34. World Health Organization. Consolidated guidelines on HIV prevention, diagnosis, treatment and care for key populations 2014 [updated July]. Available from: http://www.who.int/hiv/pub/guidelines/keypopulations/en/.
35. Vickers AJ, Bennette C, Kibel AS, Black A, Izmirlian G, Stephenson AJ, et al. Who should be included in a clinical trial of screening for bladder cancer?: a decision analysis of data from the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial. Cancer. 2013;119(1):143–9. doi: 10.1002/cncr.27692 22736219
36. Vickers AJ, Kramer BS, Baker SG. Selecting patients for randomized trials: a systematic approach based on risk group. Trials. 2006;7:30. doi: 10.1186/1745-6215-7-30 17022818
37. Schackman BR, Eggman AA. Cost-effectiveness of pre-exposure prophylaxis for HIV: a review. Curr Opin HIV AIDS. 2012;7(6):587–92. doi: 10.1097/COH.0b013e3283582c8b 23076124
38. Gomez GB, Borquez A, Case KK, Wheelock A, Vassall A, Hankins C. The cost and impact of scaling up pre-exposure prophylaxis for HIV prevention: a systematic review of cost-effectiveness modelling studies. PLoS Med. 2013;10(3):e1001401. doi: 10.1371/journal.pmed.1001401 23554579
39. Carnegie NB, Goodreau SM, Liu A, Vittinghoff E, Sanchez J, Lama JR, et al. Targeting pre-exposure prophylaxis among men who have sex with men in the United States and Peru: partnership types, contact rates, and sexual role. J Acquir Immune Defic Syndr. 2015;69(1):119–25. doi: 10.1097/QAI.0000000000000555 25942463
40. Chen A, Dowdy DW. Clinical effectiveness and cost-effectiveness of HIV pre-exposure prophylaxis in men who have sex with men: risk calculators for real-world decision-making. PLoS One. 2014;9(10):e108742. doi: 10.1371/journal.pone.0108742 25285793
41. Kessler J, Myers JE, Nucifora KA, Mensah N, Toohey C, Khademi A, et al. Evaluating the impact of prioritization of antiretroviral pre-exposure prophylaxis in New York City. AIDS. 2014.
42. Nichols BE, Boucher CAB, van der Valk M, Rijnders BJA, van de Vijver D. Cost-effectiveness analysis of pre-exposure prophylaxis for HIV-1 prevention in the Netherlands: a mathematical modelling study. Lancet Infect Dis. 2016;16(12):1423–9. doi: 10.1016/S1473-3099(16)30311-5 27665989
43. Grant RM, Anderson PL, McMahan V, Liu A, Amico KR, Mehrotra M, et al. Uptake of pre-exposure prophylaxis, sexual practices, and HIV incidence in men and transgender women who have sex with men: a cohort study. Lancet Infect Dis. 2014;14(9):820–9. doi: 10.1016/S1473-3099(14)70847-3 25065857
44. Gibson S, Grant R, Hall C, Sachs M, Gagliano J, Freeborn K, et al. San Francisco AIDS Foundation Launches PrEP Health Program in Community-Based Sexual Health Center. National HIV Prevention Conference. Vancouver, Canada: US CDC; 2015. p. 229–30.
45. Liu AY, Cohen SE, Vittinghoff E, Anderson PL, Doblecki-Lewis S, Bacon O, et al. Preexposure Prophylaxis for HIV Infection Integrated With Municipal- and Community-Based Sexual Health Services. JAMA Intern Med. 2016;176(1):75–84. doi: 10.1001/jamainternmed.2015.4683 26571482
46. Glidden DV, Amico KR, Liu AY, Hosek SG, Anderson PL, Buchbinder SP, et al. Symptoms, Side Effects and Adherence in the iPrEx Open-Label Extension. Clin Infect Dis. 2016;62(9):1172–7. doi: 10.1093/cid/ciw022 26797207
47. Cohen S, Vittinghoff E, Anderson P, Doblecki-Lewis S, Bacon O, Chege W, editors. Implementation of PrEP in STD and community health clinics in the US: high uptake and drug concentrations among MSM in the demo project. Available from http://www.iapac.org/AdherenceConference/presentations/ADH9OA377.pdf. 9th International Conference on HIV Treatment and Prevention; 2014; Miami, Florida.
48. Cohen S, Vittinghoff E, Anderson P, Doblecki-Lewis S, Bacon O, Chege W, editors. Implementation of PrEP in STD clinics: high uptake and drug detection among MSM in the demonstration project. http://www.croiconference.org/sessions/implementation-prep-std-clinics-high-uptake-and-drug-detectionamong-msm-demo-project. 21st Conference on Retroviruses and Opportunistic Infections; 2014; Boston, MA.
49. Hoagland B, Moreira RI, De Boni RB, Kallas EG, Madruga JV, Vasconcelos R, et al. High pre-exposure prophylaxis uptake and early adherence among men who have sex with men and transgender women at risk for HIV Infection: the PrEP Brasil demonstration project. J Int AIDS Soc. 2017;20(1):21472. doi: 10.7448/IAS.20.1.21472 28418232
50. Hosek SG, Rudy B, Landovitz R, Kapogiannis B, Siberry G, Rutledge B, et al. An HIV Preexposure Prophylaxis Demonstration Project and Safety Study for Young MSM. J Acquir Immune Defic Syndr. 2017;74(1):21–9. doi: 10.1097/QAI.0000000000001179 27632233
51. Anderson PL, Glidden DV, Liu A, Buchbinder S, Lama JR, Guanira JV, et al. Emtricitabine-tenofovir concentrations and pre-exposure prophylaxis efficacy in men who have sex with men. Sci Transl Med. 2012;4(151):151ra25.
52. Ruczinski I, Kooperberg C, LeBlanc M. Logic Regression. Journal of Computational and Graphical Statistics. 2003;12(3):475–511.
53. Kooperberg C, Ruczinski I. Identifying interacting SNPs using Monte Carlo logic regression. Genet Epidemiol. 2005;28(2):157–70. doi: 10.1002/gepi.20042 15532037
54. Nelson W. Theory and applications of hazard plotting for censored failure data. Technometrics. 1972;14:945–65.
55. Guyatt GH, Sackett DL, Sinclair JC, Hayward R, Cook DJ, Cook RJ. Users' guides to the medical literature. IX. A method for grading health care recommendations. Evidence-Based Medicine Working Group. JAMA. 1995;274(22):1800–4. doi: 10.1001/jama.274.22.1800 7500513
56. Sinclair JC, Cook RJ, Guyatt GH, Pauker SG, Cook DJ. When should an effective treatment be used? Derivation of the threshold number needed to treat and the minimum event rate for treatment. J Clin Epidemiol. 2001;54(3):253–62. doi: 10.1016/s0895-4356(01)00347-x 11223323
57. Vickers AJ, Cronin AM, Kattan MW, Gonen M, Scardino PT, Milowsky MI, et al. Clinical benefits of a multivariate prediction model for bladder cancer: a decision analytic approach. Cancer. 2009;115(23):5460–9. doi: 10.1002/cncr.24615 19823979
58. World Health Organization. Guideline on when to start antiretroviral therapy and on pre-exposure prophylaxis for HIV 2015 [updated [updated September]; cited 2015]. Available from: http://www.who.int/hiv/pub/guidelines/earlyrelease-arv/en/.
59. Flynn NM, Forthal DN, Harro CD, Judson FN, Mayer KH, Para MF, et al. Placebo-controlled phase 3 trial of a recombinant glycoprotein 120 vaccine to prevent HIV-1 infection. J Infect Dis. 2005;191(5):654–65. doi: 10.1086/428404 15688278
60. Bartholow BN, Buchbinder S, Celum C, Goli V, Koblin B, Para M, et al. HIV sexual risk behavior over 36 months of follow-up in the world's first HIV vaccine efficacy trial. J Acquir Immune Defic Syndr. 2005;39(1):90–101. doi: 10.1097/01.qai.0000143600.41363.78 15851919
61. Koblin B, Chesney M, Coates T, Mayer K, Agredano F, Aguilu E, et al. Effects of a behavioural intervention to reduce acquisition of HIV infection among men who have sex with men: the EXPLORE randomised controlled study. Lancet. 2004;364(9428):41–50. doi: 10.1016/S0140-6736(04)16588-4 15234855
62. Song X, Pepe MS. Evaluating markers for selecting a patient's treatment. Biometrics. 2004;60(4):874–83. doi: 10.1111/j.0006-341X.2004.00242.x 15606407
63. Janes H, Pepe MS, Bossuyt PM, Barlow WE. Measuring the performance of markers for guiding treatment decisions. Ann Intern Med. 2011;154(4):253–9. doi: 10.7326/0003-4819-154-4-201102150-00006 21320940
64. Gunter L, Zhu J, Murphy S. Variable Selection for Optimal Decision Making. Artificial Intelligence in Medicine. Lecture Notes in Computer Science. 45942007. p. 149–54.
65. Janes H, Brown MD, Huang Y, Pepe MS. An approach to evaluating and comparing biomarkers for patient treatment selection. Int J Biostat. 2014;10(1):99–121. doi: 10.1515/ijb-2012-0052 24695044
66. Kaplan EL, Meier P. Nonparametric Estimation from Incomplete Observations. Journal of the American Statistical Association. 1958;53(282):457–81.
67. Buchbinder SP, Glidden DV, Liu AY, McMahan V, Guanira JV, Mayer KH, et al. HIV pre-exposure prophylaxis in men who have sex with men and transgender women: a secondary analysis of a phase 3 randomised controlled efficacy trial. Lancet Infect Dis. 2014;14(6):468–75. doi: 10.1016/S1473-3099(14)70025-8 24613084
68. Murnane PM, Brown ER, Donnell D, Coley RY, Mugo N, Mujugira A, et al. Estimating efficacy in a randomized trial with product nonadherence: application of multiple methods to a trial of preexposure prophylaxis for HIV prevention. Am J Epidemiol. 2015;182(10):848–56. doi: 10.1093/aje/kwv202 26487343
69. Hanscom B, Janes HE, Guarino PD, Huang Y, Brown ER, Chen YQ, et al. Brief Report: Preventing HIV-1 Infection in Women Using Oral Preexposure Prophylaxis: A Meta-analysis of Current Evidence. J Acquir Immune Defic Syndr. 2016;73(5):606–8. doi: 10.1097/QAI.0000000000001160 27846073
70. Fonner VA, Dalglish SL, Kennedy CE, Baggaley R, O'Reilly KR, Koechlin FM, et al. Effectiveness and safety of oral HIV preexposure prophylaxis for all populations. AIDS. 2016;30(12):1973–83. doi: 10.1097/QAD.0000000000001145 27149090
71. Hosek S, Rudy B, Landovitz R, Kapogiannis B, Siberry G, Rutledge B, et al. An HIV pre-exposure prophylaxis (PrEP) demonstration project and safety study for young MSM. J Acquir Immune Defic Syndr. 2016;74(1):21–9.
72. Koblin BA, Mayer K, Eshelman SH, Wang L, Mannheimer S, del Rio C, et al. Correlates of HIV acquisition in a cohort of black men who have sex with men in the United States: HIV Prevention Trials Network (HPTN) 061. PLoS ONE. 2013;8(7):e70413. doi: 10.1371/journal.pone.0070413 23922989
73. Halloran ME, Longini J, I. M., Struchiner CJ. Design and Analysis of Vaccine StudiesSpringer; 2010.
74. McAuliffe TL, DiFranceisco W, Reed BR. Effects of question format and collection mode on the accuracy of retrospective surveys of health risk behavior: a comparison with daily sexual activity diaries. Health Psychol. 2007;26(1):60–7. doi: 10.1037/0278-6133.26.1.60 17209698
75. Schroder KE, Carey MP, Vanable PA. Methodological challenges in research on sexual risk behavior: I. Item content, scaling, and data analytical options. Ann Behav Med. 2003;26(2):76–103. doi: 10.1207/s15324796abm2602_02 14534027
76. Mirzaei M, Ahmadi K, Saadat SH, Ramezani MA. Instruments of High Risk Sexual Behavior Assessment: A Systematic Review. Mater Sociomed. 2016;28(1):46–50. doi: 10.5455/msm.2016.28.46-50 27047267
77. Zheng W, Balzer L, van der Laan M, Petersen M, Collaboration S. Constrained binary classification using ensemble learning: an application to cost-efficient targeted PrEP strategies. Stat Med. 2018;37(2):261–79. doi: 10.1002/sim.7296 28384841
Článok vyšiel v časopise
PLOS One
2019 Číslo 9
- Metamizol jako analgetikum první volby: kdy, pro koho, jak a proč?
- Nejasný stín na plicích – kazuistika
- Masturbační chování žen v ČR − dotazníková studie
- Těžké menstruační krvácení může značit poruchu krevní srážlivosti. Jaký management vyšetření a léčby je v takovém případě vhodný?
- Fixní kombinace paracetamol/kodein nabízí synergické analgetické účinky
Najčítanejšie v tomto čísle
- Graviola (Annona muricata) attenuates behavioural alterations and testicular oxidative stress induced by streptozotocin in diabetic rats
- CH(II), a cerebroprotein hydrolysate, exhibits potential neuro-protective effect on Alzheimer’s disease
- Comparison between Aptima Assays (Hologic) and the Allplex STI Essential Assay (Seegene) for the diagnosis of Sexually transmitted infections
- Assessment of glucose-6-phosphate dehydrogenase activity using CareStart G6PD rapid diagnostic test and associated genetic variants in Plasmodium vivax malaria endemic setting in Mauritania