Повышение качества отчетов о наблюдательных исследованиях в эпидемиологии (STROBE): разъяснения и уточнения

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Большинство медицинских исследований являются наблюдательными (observational). Сообщения о таких исследованиях часто невысокого качества, что затрудняет оценку сильных и слабых сторон работы, а также обобщаемости (generalizability) её результатов. Принимая во внимание эмпирические свидетельства и теоретические соображения, группа методологов, исследователей и научных редакторов разработала рекомендации «Повышение качества отчётов о наблюдательных исследованиях в эпидемиологии (STROBE): разъяснения и уточнения». Рекомендации STROBE содержат 22 пункта, связанных с оформлением следующих разделов научных статей: название, аннотация, введение, методы, результаты и их обсуждение, при этом 18 пунктов являются общими для когортных исследований (cohort studies), исследований «случай–контроль» (case-control studies) и одномоментных исследований (cross-sectional studies); 4 пункта специфичны для каждого из указанных дизайнов исследований (study designs). STROBE ― руководство для авторов, необходимое для повышения качества отчётов о наблюдательных исследованиях, облегчающее критическую оценку исследования и его интерпретацию рецензентами, редакторами журналов и читателями. Цель этой разъясняющей и уточняющей статьи ― способствовать более широкому применению, пониманию и распространению стандартов STROBE. В ней даётся разъяснение смысла и обоснование применения каждого пункта руководства (checklist). По каждому пункту приводятся один или несколько опубликованных примеров правильного представления исследований и, при возможности, библиографические ссылки на подходящие эмпирические исследования и методологическую литературу. Представлены примеры потоковых диаграмм (flow diagrams) для описания последовательности исследования. Рекомендации STROBE, настоящая статья и соответствующий веб-сайт (http://www.strobe-statement.org/) должны стать полезным источником для повышения качества отчётов о результатах наблюдательных исследований.

Настоящая статья является русскоязычным переводом оригинальной публикации [Vandenbroucke JP, von Elm E, Altman DG, Gotzsche PC, Mulrow CD, et al. Strengthening the Reporting of Observational Studies in Epidemiology (STROBE): Explanation and Elaboration. PLoS Med. 2007;4(10):e297. doi: 10.1371/journal.pmed.0040297] под редакцией доктор медицинских наук Р.Т. Сайгитова.

Об авторах

Jan P. Vandenbroucke

Leiden University Medical Center

Email: strobe@ispm.unibe.ch
ORCID iD: 0000-0001-5668-6716

Department of Clinical Epidemiology

Нидерланды, Лейден

Erik von Elm

University of Bern; University Medical Centre

Email: strobe@ispm.unibe.ch
ORCID iD: 0000-0002-7412-0406

Institute of Social & Preventive Medicine (ISPM) of the University of Bern; Department of Medical Biometry and Medical Informatics of the University Medical Centre

Швейцария, Берн; Фрайбург, Германия

Douglas G. Altman

Cancer Research UK/NHS Centre for Statistics in Medicine

Email: strobe@ispm.unibe.ch
ORCID iD: 0000-0002-7183-4083
Великобритания, Оксфорд

Peter C. Gotzsche

Nordic Cochrane Centre, Rigshospitalet

Email: strobe@ispm.unibe.ch
Дания, Копенгаген

Cynthia D. Mulrow

University of Texas Health Science Center

Email: strobe@ispm.unibe.ch
ORCID iD: 0000-0002-4768-4492
США, Сан-Антонио

Stuart J. Pocock

London School of Hygiene and Tropical Medicine

Email: strobe@ispm.unibe.ch
ORCID iD: 0000-0003-2212-4007

Medical Statistics Unit

Великобритания, Лондон

Charles Poole

University of North Carolina School of Public Health

Email: strobe@ispm.unibe.ch

Department of Epidemiology

США, Чапел-Хилл

James J. Schlesselman

University of Pittsburgh Graduate School of Public Health; University of Pittsburgh Cancer Institute

Email: strobe@ispm.unibe.ch

Department of Biostatistics

США, Питтсбург; Питтсбург

Matthias Egger

University of Bern; University of Bristol

Автор, ответственный за переписку.
Email: strobe@ispm.unibe.ch
ORCID iD: 0000-0001-7462-5132

Institute of Social & Preventive Medicine (ISPM) of the University of Bern; Department of Social Medicine of the University of Bristol

Великобритания, Берн, Швейцария; Бристоль

Список литературы

  1. Glasziou P., Vandenbroucke J.P., Chalmers I. Assessing the quality of research//BMJ. 2004. Vol. 328, N 7430. P. 39–41. doi: 10.1136/bmj.328.7430.39
  2. Funai E.F., Rosenbush E.J., Lee M.J., Del Priore G. Distribution of study designs in four major US journals of obstetrics and gynecology//Gynecol Obstet Invest. 200. Vol. 151, N 1. P. 8–11. doi: 10.1159/000052882
  3. Scales C.D., Norris R.D., Peterson B.L., et al. Clinical research and statistical methods in the urology literature//J Urol. 2005. Vol. 174, N (4 Pt 1). P. 1374–1379. doi: 10.1097/01.ju.0000173640.91654.b5
  4. Pocock S.J., Collier T.J., Dandreo K.J., et al. Issues in the reporting of epidemiological studies: a survey of recent practice//BMJ. 2004. Vol. 329, N 7471. P. 883. doi: 10.1136/bmj.38250.571088.55
  5. Tooth L., Ware R., Bain C., et al. Quality of reporting of observational longitudinal research//Am J Epidemiol. 2005. Vol. 161, N 3. P. 280–288. doi: 10.1093/aje/kwi042
  6. Von Elm E., Altman D.G., Egger M., et al. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement: guidelines for reporting observational studies//Epidemiology. 2007. Vol. 18, N 6. P. 800–804. doi: 10.1097/EDE.0b013e3181577654
  7. Mihailovic A., Bell C.M., Urbach D.R. Users’ guide to the surgical literature. Case-control studies in surgical journals//Can J Surg. 2005. Vol. 48, N 2. P. 148–151.
  8. Rushton L. Reporting of occupational and environmental research: use and misuse of statistical and epidemiological methods//Occup Environ Med. 2000. Vol. 57, N 1. P. 1–9. doi: 10.1136/oem.57.1.1
  9. Rothman K.J. No adjustments are needed for multiple comparisons//Epidemiology. 1990. Vol. 1, N 1. P. 43–46. doi: 10.1097/00001648-199001000-00010
  10. Moonesinghe R., Khoury M.J., Janssens A.C. Most published research findings are false-but a little replication goes a long way//PLoS Med. 2007. Vol. 4, N 2. P. e28. doi: 10.1371/journal.pmed.0040028
  11. Jenicek M. Clinical Case Reporting. Evidence-Based Medicine. Oxford: Butterworth-Heinemann; 1999. 117 p.
  12. Vandenbroucke J.P. In defense of case reports and case series//Ann Intern Med. 2001. Vol. 134, N 4. P. 330–334. doi: 10.7326/0003-4819-134-4-200102200-00017
  13. Bossuyt P.M., Reitsma J.B., Bruns D.E., et al. Towards complete and accurate reporting of studies of diagnostic accuracy: The STARD Initiative//Ann Intern Med. 2003. Vol. 138, N 1. P. 40–44. doi: 10.7326/0003-4819-138-1-200301070-00010
  14. McShane L.M., Altman D.G., Sauerbrei W., et al. REporting recommendations for tumour MARKer prognostic studies (REMARK)//Br J Cancer. 2005. Vol. 93, N 4. P. 387–391. doi: 10.1038/sj.bjc.6602678
  15. Ioannidis J.P., Gwinn M., Little J., et al. A road map for efficient and reliable human genome epidemiology//Nat Genet. 2006. Vol. 38, N 1. P. 3–5. doi: 10.1038/ng0106-3
  16. Rodrigues L., Kirkwood B.R. Case-control designs in the study of common diseases: updates on the demise of the rare disease assumption and the choice of sampling scheme for controls//Int J Epidemiol. 1990. Vol. 19, N 1. P. 205–213. doi: 10.1093/ije/19.1.205
  17. Rothman K.J., Greenland S. Case-Control Studies. In: Rothman KJ, Greenland S, editors. Modern epidemiology. 2nd ed. Philadelphia: Lippincott Raven, 1998. pp. 93–114.
  18. Forand S.P. Leukaemia incidence among workers in the shoe and boot manufacturing industry: a case-control study//Environ Health. 2004. Vol. 3, N 1. P. 7. doi: 10.1186/1476-069X-3-7
  19. Benson K., Hartz A.J. A comparison of observational studies and randomized, controlled trials//N Engl J Med. 2000. Vol. 342, N 25. P. 1878–1886. doi: 10.1056/NEJM200006223422506
  20. Gøtzsche P.C., Harden A. Searching for non-randomised studies. Draft chapter 3. Cochrane Non-Randomised Studies Methods Group, 2002. Available from: http://www.cochrane.dk/nrsmg. Accessed 10 September 2007.
  21. Lohse N., Hansen A.B., Pedersen G., et al. Survival of persons with and without HIV infection in Denmark, 1995-2005//Ann Intern Med. 2007. Vol. 146, N 2. P. 87–95. doi: 10.7326/0003-4819-146-2-200701160-00003
  22. American Journal of Epidemiology. 2007. Information for authors. Available from: http://www.oxfordjournals.org/aje/for_authors/index.html. Accessed 10 September 2007.
  23. Haynes R.B., Mulrow C.D., Huth E.J., et al. More informative abstracts revisited//Ann Intern Med. 1990. Vol. 113, N 1. P. 69–76. doi: 10.7326/0003-4819-113-1-69
  24. Taddio A., Pain T., Fassos F.F., et al. Quality of nonstructured and structured abstracts of original research articles in the British Medical Journal, the Canadian Medical Association Journal and the Journal of the American Medical Association//CMAJ. 1994. Vol. 150, N 10. P. 1611–1615.
  25. Hartley J., Sydes M. Which layout do you prefer? An analysis of readers’ preferences for different typographic layouts of structured abstracts//J Inform Sci. 1996. Vol. 22, N 1. P. 27–37. doi: 10.1177/016555159602200103
  26. Viner R.M., Cole T.J. Adult socioeconomic, educational, social, and psychological outcomes of childhood obesity: a national birth cohort study//BMJ. 2005. Vol. 330, N 7504. P. 1354. doi: 10.1136/bmj.38453.422049.E0
  27. McCauley J., Kern D.E., Kolodner K., et al. The “battering syndrome”: prevalence and clinical characteristics of domestic violence in primary care internal medicine practices//Ann Intern Med. 1995. Vol. 123, N 10. P. 737–746. doi: 10.7326/0003-4819-123-10-199511150-00001
  28. McEvoy S.P., Stevenson M.R., McCartt A.T., et al. Role of mobile phones in motor vehicle crashes resulting in hospital attendance: a case-crossover study//BMJ. 2005. Vol. 331, N 7514. P. 428. doi: 10.1136/bmj.38537.397512.55
  29. Vandenbroucke J.P. Prospective or retrospective: what’s in a name?//BMJ. 1991. Vol. 302, N 6771. P. 249–250. doi: 10.1136/bmj.302.6771.249
  30. Last J.M. A Dictionary of Epidemiology. New York: Oxford University Press, 2000.
  31. Miettinen O.S. Theoretical Epidemiology: principles of occurrence research in medicine. New York: Wiley, 1985. Р. 64–66.
  32. Rothman K.J., Greenland S. Types of Epidemiologic Studies. In: Rothman KJ, Greenland S, editors. Modern epidemiology. 2nd ed. Lippincott Raven; 1998. Р. 74–75.
  33. MacMahon B., Trichopoulos D. Epidemiology, principles and methods. 2nd ed. Boston: Little, Brown; 1996. 81 p. doi: 10.1016/S0033-3506(97)00047-4
  34. Lilienfeld A.M. Foundations of Epidemiology. New York: Oxford University Press, 1976.
  35. Ridker P.M., Hennekens C.H., Lindpaintner K., et al. Mutation in the gene coding for coagulation factor V and the risk of myocardial infarction, stroke, and venous thrombosis in apparently healthy men//N Engl J Med. 1995. Vol. 332, N 14. P. 912–917. doi: 10.1056/NEJM199504063321403
  36. Goodman K.J., O’Rourke K., Day R.S., et al. Dynamics of Helicobacter pylori infection in a US-Mexico cohort during the first two years of life//Int J Epidemiol. 2005. Vol. 34, N 6. P. 1348–1355. doi: 10.1093/ije/dyi152
  37. Altman D.G., De Stavola B.L., Love S.B., Stepniewska K.A. Review of survival analyses published in cancer journals//Br J Cancer. 1995. Vol. 72, N 2. P. 511–518. doi: 10.1038/bjc.1995.364
  38. Cerhan J.R., Wallace R.B., Folsom A.R., et al. Transfusion history and cancer risk in older women//Ann Intern Med. 1993. Vol. 119, N 1. P. 8–15. doi: 10.7326/0003-4819-119-1-199307010-00002
  39. Freeman L.E., Dennis L.K., Lynch C.F., et al. Toenail arsenic content and cutaneous melanoma in Iowa//Am J Epidemiol. 2004. Vol. 160, N 7. P. 679–687. doi: 10.1093/aje/kwh267
  40. Canto J.G., Allison J.J., Kiefe C.I., et al. Relation of race and sex to the use of reperfusion therapy in Medicare beneficiaries with acute myocardial infarction//N Engl J Med. 2000. Vol. 342, N 15. P. 1094–1100. doi: 10.1056/NEJM200004133421505
  41. Metzkor-Cotter E., Kletter Y., Avidor B., et al. Long-term serological analysis and clinical follow-up of patients with cat scratch disease//Clin Infect Dis. 2003. Vol. 37, N 9. P. 1149–1154. doi: 10.1086/378738
  42. Johnson E.S. Bias on withdrawing lost subjects from the analysis at the time of loss, in cohort mortality studies, and in follow-up methods//J Occup Med. 1990. Vol. 32, N 3. P. 250–254. doi: 10.1097/00043764-199003000-00013
  43. Berkson J. Limitations of the application of fourfold table analysis to hospital data//Biom Bull. 1946. Vol. 2, N 3. P. 47. doi: 10.2307/3002000
  44. Feinstein A.R., Walter S.D., Horwitz R.I. An analysis of Berkson’s bias in case-control studies//J Chronic Dis. 1986. Vol. 39, N 7. P. 495–504. doi: 10.1016/0021-9681(86)90194-3
  45. Jick H., Vessey M.P. Case-control studies in the evaluation of drug-induced illness//Am J Epidemiol. 1978. Vol. 107, N 1. P. 1–7. doi: 10.1093/oxfordjournals.aje.a112502
  46. Hackam D.G., Mamdani M., Li P., Redelmeier D.A. Statins and sepsis in patients with cardiovascular disease: a population-based cohort analysis//Lancet. 2006. Vol. 367, N 9508. P. 413–418. doi: 10.1016/S0140-6736(06)68041-0
  47. Smeeth L., Cook C., Fombonne E., et al. MMR vaccination and pervasive developmental disorders: a case-control study//Lancet. 2004. Vol. 364, N 9438. P. 963–969. doi: 10.1016/S0140-6736(04)17020-7
  48. Costanza M.C. Matching//Prev Med. 1995. Vol. 24, N 5. P. 425–433. doi: 10.1006/pmed.1995.1069
  49. Sturmer T., Brenner H. Flexible matching strategies to increase power and efficiency to detect and estimate gene-environment interactions in case-control studies//Am J Epidemiol. 2002. Vol. 155, N 7. P. 593–602. doi: 10.1093/aje/155.7.593
  50. Rothman K.J., Greenland S. Matching. In: Rothman KJ, Greenland S, editors. 2nd ed. Modern epidemiology. Lippincott Raven; 1998. Р. 147–161.
  51. Szklo M.F., Nieto J. Epidemiology, Beyond the Basics. Sudbury (MA): Jones and Bartlett; 2000. Р. 40–51.
  52. Cole P., MacMahon B. Attributable risk percent in case-control studies//Br J Prev Soc Med. 1971. Vol. 25, N 4. P. 242–244. doi: 10.1136/jech.25.4.242
  53. Gissler M., Hemminki E. The danger of overmatching in studies of the perinatal mortality and birthweight of infants born after assisted conception//Eur J Obstet Gynecol Reprod Biol. 1996. Vol. 69, N 2. P. 73–75. doi: 10.1016/0301-2115(95)02517-0
  54. Gefeller O., Pfahlberg A., Brenner H., Windeler J. An empirical investigation on matching in published case-control studies//Eur J Epidemiol. 1998. Vol. 14, N 4. P. 321–325. doi: 10.1023/A:1007497104800
  55. Artama M., Ritvanen A., Gissler M., et al. Congenital structural anomalies in offspring of women with epilepsy-a population-based cohort study in Finland//Int J Epidemiol. 2006. Vol. 35, N 2. P. 280–287. doi: 10.1093/ije/dyi234
  56. Ebrahim S. Cohorts, infants and children//Int J Epidemiol. 2004. Vol. 33, N 6. P. 1165–1166. doi: 10.1093/ije/dyh368
  57. Walker M., Whincup P.H., Shaper A.G. The British Regional Heart Study 1975-2004//Int J Epidemiol. 2004. Vol. 33, N 6. P. 1185–1192. doi: 10.1093/ije/dyh295
  58. Wieland S., Dickersin K. Selective exposure reporting and Medline indexing limited the search sensitivity for observational studies of the adverse effects of oral contraceptives//J Clin Epidemiol. 2005. Vol. 58, N 6. P. 560–567. doi: 10.1016/j.jclinepi.2004.11.018
  59. Anderson H.R., Atkinson R.W., Peacock J.L., et al. Ambient particulate matter and health effects: publication bias in studies of short-term associations//Epidemiology. 2005. Vol. 16, N 2. P. 155–163. doi: 10.1097/01.ede.0000152528.22746.0f
  60. Winkelmayer W.C., Stampfer M.J., Willett W.C., Curhan G.C. Habitual caffeine intake and the risk of hypertension in women//JAMA. 2005. Vol. 294, N 18. P. 2330–2335. doi: 10.1001/jama.294.18.2330
  61. Lukanova A., Soderberg S., Kaaks R., et al. Serum adiponectin is not associated with risk of colorectal cancer//Cancer Epidemiol Biomarkers Prev. 2006. Vol. 15, N 2. P. 401–402. doi: 10.1158/1055-9965.EPI-05-0836
  62. Becher H. The concept of residual confounding in regression models and some applications//Stat Med. 1992. Vol. 11, N 13. P. 1747–1758. doi: 10.1002/sim.4780111308
  63. Brenner H., Blettner M. Controlling for continuous confounders in epidemiologic research//Epidemiology. 1997. Vol. 8, N 4. P. 429–434. doi: 10.1097/00001648-199707000-00014
  64. Phillips M.R., Yang G., Zhang Y., et al. Risk factors for suicide in China: a national case-control psychological autopsy study//Lancet. 2002. Vol. 360, N 9347. P. 1728–1736. doi: 10.1016/S0140-6736(02)11681-3
  65. Pasquale L.R., Kang J.H., Manson J.E., et al. Prospective study of type 2 diabetes mellitus and risk of primary open-angle glaucoma in women//Ophthalmology. 2006. Vol. 113, N 7. P. 1081–1086. doi: 10.1016/j.ophtha.2006.01.066
  66. Craig S.L., Feinstein A.R. Antecedent therapy versus detection bias as causes of neoplastic multimorbidity//Am J Clin Oncol. 1999. Vol. 22, N 1. P. 51–56. doi: 10.1097/00000421-199902000-00013
  67. Rogler L.H., Mroczek D.K., Fellows M., Loftus S.T. The neglect of response bias in mental health research//J Nerv Ment Dis. 2001. Vol. 189, N 3. P. 182–187. doi: 10.1097/00005053-200103000-00007
  68. Murphy E.A. The logic of medicine. Baltimore: Johns Hopkins University Press, 1976.
  69. Sackett D.L. Bias in analytic research//J Chronic Dis. 1979. Vol. 32, N 1-2. P. 51–63. doi: 10.1016/0021-9681(79)90012-2
  70. Johannes C.B., Crawford S.L., McKinlay J.B. Interviewer effects in a cohort study. Results from the Massachusetts Women’s Health Study//Am J Epidemiol. 1997. Vol. 146, N 5. P. 429–438. doi: 10.1093/oxfordjournals.aje.a009296
  71. Bloemenkamp K.W., Rosendaal F.R., Buller H.R., et al. Risk of venous thrombosis with use of current low-dose oral contraceptives is not explained by diagnostic suspicion and referral bias//Arch Intern Med. 1999. Vol. 159, N 1. P. 65–70. doi: 10.1001/archinte.159.1.65
  72. Feinstein A.R. Clinical epidemiology: the architecture of clinical research. Philadelphia: W.B. Saunders, 1985.
  73. Yadon Z.E., Rodrigues L.C., Davies C.R., Quigley M.A. Indoor and peridomestic transmission of American cutaneous leishmaniasis in northwestern Argentina: a retrospective case-control study//Am J Trop Med Hyg. 2003. Vol. 68, N 5. P. 519–526. doi: 10.4269/ajtmh.2003.68.519
  74. Anoop S., Saravanan B., Joseph A., et al. Maternal depression and low maternal intelligence as risk factors for malnutrition in children: a community based case-control study from South India//Arch Dis Child. 2004. Vol. 89, N 4. P. 325–329. doi: 10.1136/adc.2002.009738
  75. Carlin J.B., Doyle L.W. Sample size//J Paediatr Child Health. 2002. Vol. 38, N 3. P. 300–304. doi: 10.1046/j.1440-1754.2002.00855.x
  76. Rigby A.S., Vail A. Statistical methods in epidemiology. II: A commonsense approach to sample size estimation//Disabil Rehabil. 1998. Vol. 20, N 11. P. 405–410. doi: 10.3109/09638289809166102
  77. Schulz K.F., Grimes D.A. Sample size calculations in randomised trials: mandatory and mystical//Lancet. 2005. Vol. 365, N 9467. P. 1348–1353. doi: 10.1016/S0140-6736(05)61034-3
  78. Drescher K., Timm J., Jockel K.H. The design of case-control studies: the effect of confounding on sample size requirements//Stat Med. 1990. Vol. 9, N 7. P. 765–776. doi: 10.1002/sim.4780090706
  79. Devine O.J., Smith J.M. Estimating sample size for epidemiologic studies: the impact of ignoring exposure measurement uncertainty//Stat Med. 1998. Vol. 17, N 12. P. 1375–1389. doi: 10.1002/(SICI)1097-0258(19980630)17:12<1375::AID-SIM857>3.0.CO;2-D
  80. Linn S., Levi L., Grunau P.D., et al. Effect measure modification and confounding of severe head injury mortality by age and multiple organ injury severity//Ann Epidemiol. 2007. Vol. 17, N 2. P. 142–147. doi: 10.1016/j.annepidem.2006.08.004
  81. Altman D.G., Lausen B., Sauerbrei W., Schumacher M. Dangers of using “optimal” cutpoints in the evaluation of prognostic factors//J Natl Cancer Inst. 1994. Vol. 86, N 11. P. 829–835. doi: 10.1093/jnci/86.11.829
  82. Royston P., Altman D.G., Sauerbrei W. Dichotomizing continuous predictors in multiple regression: a bad idea//Stat Med. 2006. Vol. 25, N 1. P. 127–141. doi: 10.1002/sim.2331
  83. Greenland S. Avoiding power loss associated with categorization and ordinal scores in dose-response and trend analysis//Epidemiology. 1995. Vol. 6, N 4. P. 450–454. doi: 10.1097/00001648-199507000-00025
  84. Royston P., Ambler G., Sauerbrei W. The use of fractional polynomials to model continuous risk variables in epidemiology//Int J Epidemiol. 1999. Vol. 28, N 5. P. 964–974. doi: 10.1093/ije/28.5.964
  85. MacCallum R.C., Zhang S., Preacher K.J., Rucker D.D. On the practice of dichotomization of quantitative variables//Psychol Methods. 2002. Vol. 7, N 1. P. 19–40. doi: 10.1037/1082-989X.7.1.19
  86. Altman D.G. Categorizing continuous variables. In: Armitage P, Colton T, editors. Encyclopedia of biostatistics. 2nd ed. Chichester: John Wiley; 2005. Р. 708–711. doi: 10.1002/0470011815.b2a10012
  87. Cohen J. The cost of dichotomization//Applied Psychological Measurement. 1983. Vol. 7, N 3. P. 249–253. doi: 10.1177/014662168300700301
  88. Zhao L.P., Kolonel L.N. Efficiency loss from categorizing quantitative exposures into qualitative exposures in case-control studies//Am J Epidemiol. 1992. Vol. 136, N 4. P. 464–474. doi: 10.1093/oxfordjournals.aje.a116520
  89. Cochran W.G. The effectiveness of adjustment by subclassification in removing bias in observational studies//Biometrics. 1968. Vol. 24, N 2. P. 295–313. doi: 10.2307/2528036
  90. Clayton D., Hills M. Models for dose-response (Chapter 25). Statistical Models in Epidemiology. Oxford: Oxford University Press, 1993. Р. 249–260.
  91. Cox D.R. Note on grouping//J Am Stat Assoc. 1957. Vol. 52, N 280. P. 543–547. doi: 10.1080/01621459.1957.10501411
  92. Il’yasova D., Hertz-Picciotto I., Peters U., et al. Choice of exposure scores for categorical regression in meta-analysis: a case study of a common problem//Cancer Causes Control. 2005. Vol. 16, N 4. P. 383–388. doi: 10.1007/s10552-004-5025-x
  93. Berglund A., Alfredsson L., Cassidy J.D., et al. The association between exposure to a rear-end collision and future neck or shoulder pain: a cohort study//J Clin Epidemiol. 2000. Vol. 53, N 11. P. 1089–1094. doi: 10.1016/S0895-4356(00)00225-0
  94. Slama R., Werwatz A. Controlling for continuous confounding factors: non- and semiparametric approaches//Rev Epidemiol Sante Publique. 2005. Vol. 53, N Spec No 2. P. 2S65–80. doi: 10.1016/S0398-7620(05)84769-8
  95. Greenland S. Introduction to regression modelling (Chapter 21). In: Rothman KJ, Greenland S, editors. Modern epidemiology. 2nd ed: Lippincott Raven, 1998. Р. 401–432.
  96. Thompson W.D. Statistical analysis of case-control studies//Epidemiol Rev. 1994. Vol. 16, N 1. P. 33–50. doi: 10.1093/oxfordjournals.epirev.a036143
  97. Schlesselman J.J. Logistic regression for case-control studies (Chapter 8.2). Case-control studies Design, conduct, analysis. New York, Oxford: Oxford University Press, 1982. Р. 235–241.
  98. Clayton D., Hills M. Choice and interpretation of models (Chapter 27). Statistical Models in Epidemiology. Oxford: Oxford University Press, 1993. Р. 271–281.
  99. Altman D.G., Gore S.M., Gardner M.J., Pocock S.J. Statistical guidelines for contributors to medical journals//Br Med J. 1983. Vol. 286, N 6376. P. 1489–1493. doi: 10.1136/bmj.286.6376.1489
  100. International Committee of Medical Journal Editors Uniform requirements for manuscripts submitted to biomedical journals//N Engl J Med. 1997. Vol. 336. P. 309–315. [Electronic version updated February 2006, Available from at http://www.icmje.org/]. doi: 10.1056/NEJM199701233360422
  101. Mullner M., Matthews H., Altman D.G. Reporting on statistical methods to adjust for confounding: a cross-sectional survey//Ann Intern Med. 2002. Vol. 136, N 2. P. 122–126. doi: 10.7326/0003-4819-136-2-200201150-00009
  102. Olsen J., Basso O. Re: Residual confounding//Am J Epidemiol. 1999. Vol. 149, N 3. P. 290. doi: 10.1093/oxfordjournals.aje.a009805
  103. Hallan S., de Mutsert R., Carlsen S., et al. Obesity, smoking, and physical inactivity as risk factors for CKD: are men more vulnerable?//Am J Kidney Dis. 2006. Vol. 47, N 3. P. 396–405. doi: 10.1053/j.ajkd.2005.11.027
  104. Gotzsche P.C. Believability of relative risks and odds ratios in abstracts: cross sectional study//BMJ. 2006. Vol. 333, N 7561. P. 231–234. doi: 10.1136/bmj.38895.410451.79
  105. Szklo M..F, Nieto J. Communicating Results of Epidemiologic Studies (Chapter 9). Epidemiology, Beyond the Basics. Sudbury (MA): Jones and Bartlett, 2000. Р. 408–430.
  106. Chandola T., Brunner E., Marmot M. Chronic stress at work and the metabolic syndrome: prospective study//BMJ. 2006. Vol. 332, N 7540. P. 521–525. doi: 10.1136/bmj.38693.435301.80
  107. Vach W. Blettner M. Biased estimation of the odds ratio in case-control studies due to the use of ad hoc methods of correcting for missing values for confounding variables//Am J Epidemiol. 1991. Vol. 134, N 8. P. 895–907. doi: 10.1093/oxfordjournals.aje.a116164
  108. Little R.J., Rubin D.B. A taxonomy of missing-data methods (Chapter 1.4.). Statistical Analysis with Missing Data. New York: Wiley, 2002. Р. 19–23. doi: 10.1002/9781119013563
  109. Ware J.H. Interpreting incomplete data in studies of diet and weight loss//N Engl J Med. 2003. Vol. 348, N 21. P. 2136–2137. doi: 10.1056/NEJMe030054
  110. Rubin D.B. Inference and missing data//Biometrika. 1976. Vol. 63, N 3. P. 581–592. doi: 10.1093/biomet/63.3.581
  111. Schafer J.L. Analysis of Incomplete Multivariate Data. London: Chapman & Hall, 1997. doi: 10.1201/9781439821862
  112. Lipsitz S.R., Ibrahim J.G., Chen M.H., Peterson H. Non-ignorable missing covariates in generalized linear models//Stat Med. 1999. Vol. 18, N 17-18. P. 2435–2448. doi: 10.1002/(SICI)1097-0258(19990915/30)18:17/18<2435::AID-SIM267>3.0.CO;2-B
  113. Rotnitzky A., Robins J. Analysis of semi-parametric regression models with non-ignorable non-response//Stat Med. 1997. Vol. 16, N 1-3. P. 81–102. doi: 10.1002/(SICI)1097-0258(19970115)16:1<81::AID-SIM473>3.0.CO;2-0
  114. Rubin D.B. Multiple Imputation for Nonresponse in Surveys. New York: John Wiley; 1987. doi: 10.1002/9780470316696
  115. Barnard J., Meng X.L. Applications of multiple imputation in medical studies: from AIDS to NHANES//Stat Methods Med Res. 1999. Vol. 8, N 1. P. 17–36. doi: 10.1177/096228029900800103
  116. Braitstein P., Brinkhof M.W., Dabis F., et al. Mortality of HIV-1-infected patients in the first year of antiretroviral therapy: comparison between low-income and high-income countries//Lancet. 2006. Vol. 367, N 9513. P. 817–824. doi: 10.1016/S0140-6736(06)68337-2
  117. Purandare N., Burns A., Daly K.J., et al. Cerebral emboli as a potential cause of Alzheimer’s disease and vascular dementia: case-control study//BMJ. 2006. Vol. 332, N 7550. P. 1119–1124. doi: 10.1136/bmj.38814.696493.AE
  118. Steyn K., Gaziano T.A., Bradshaw D., et al. Hypertension in South African adults: results from the Demographic and Health Survey, 1998//J Hypertens. 2001. Vol. 19, N 10. P. 1717–1725. doi: 10.1097/00004872-200110000-00004
  119. Lohr S.L. Design Effects (Chapter 7.5). Sampling: Design and Analysis. Pacific Grove (CA): Duxbury Press, 1999.
  120. Dunn N.R., Arscott A., Thorogood M. The relationship between use of oral contraceptives and myocardial infarction in young women with fatal outcome, compared to those who survive: results from the MICA case-control study//Contraception. 2001. Vol. 63, N 2. P. 65–69. doi: 10.1016/S0010-7824(01)00172-X
  121. Rothman K.J., Greenland S. Basic Methods for Sensitivity Analysis and External Adjustment. In: Rothman KJ, Greenland S, editors. Modern epidemiology. 2nd ed. Lippincott Raven; 1998. Р. 343–357.
  122. Custer B., Longstreth W.T., Phillips L.E., et al. Hormonal exposures and the risk of intracranial meningioma in women: a population-based case-control study//BMC Cancer. 2006. Vol. 6. P. 152. doi: 10.1186/1471-2407-6-152
  123. Wakefield M.A., Chaloupka F.J., Kaufman N.J., et al. Effect of restrictions on smoking at home, at school, and in public places on teenage smoking: cross sectional study//BMJ. 2000. Vol. 321, N 7257. P. 333–337. doi: 10.1136/bmj.321.7257.333
  124. Greenland S. The impact of prior distributions for uncontrolled confounding and response bias: a case study of the relation of wire codes and magnetic fields to childhood leukemia//J Am Stat Assoc. 2003. Vol. 98, N 461. P. 47–54. doi: 10.1198/01621450338861905
  125. Lash T.L., Fink A.K. Semi-automated sensitivity analysis to assess systematic errors in observational data//Epidemiology. 2003. Vol. 14, N 4. P. 451–458. doi: 10.1097/01.EDE.0000071419.41011.cf
  126. Phillips C.V. Quantifying and reporting uncertainty from systematic errors//Epidemiology. 2003. Vol. 14, N 4. P. 459–466. doi: 10.1097/01.ede.0000072106.65262.ae
  127. Cornfield J., Haenszel W., Hammond E.C., et al. Smoking and lung cancer: recent evidence and a discussion of some questions//J Natl Cancer Inst. 1959. Vol. 22, N 1. P. 173–203.
  128. Langholz B. Factors that explain the power line configuration wiring code-childhood leukemia association: what would they look like?//Bioelectromagnetics. 2001. Suppl 5. P. S19–31. doi: 10.1002/1521-186x(2001)22:5+<::aid-bem1021>3.3.co;2-9
  129. Eisner M.D., Smith A.K., Blanc P.D. Bartenders’ respiratory health after establishment of smoke-free bars and taverns//JAMA. 1998. Vol. 280, N 22. P. 1909–1914. doi: 10.1001/jama.280.22.1909
  130. Dunne M.P. Martin N.G., Bailey J.M., et al. Participation bias in a sexuality survey: psychological and behavioural characteristics of responders and non-responders//Int J Epidemiol. 1997. Vol. 26, N 4. P. 844–854. doi: 10.1093/ije/26.4.844
  131. Schuz J., Kaatsch P., Kaletsch U., et al. Association of childhood cancer with factors related to pregnancy and birth//Int J Epidemiol. 1999. Vol. 28, N 4. P. 631–639. doi: 10.1093/ije/28.4.631
  132. Cnattingius S., Zack M., Ekbom A., et al. Prenatal and neonatal risk factors for childhood myeloid leukemia//Cancer Epidemiol Biomarkers Prev. 1995. Vol. 4, N 5. P. 441–445.
  133. Schuz J. Non-response bias as a likely cause of the association between young maternal age at the time of delivery and the risk of cancer in the offspring//Paediatr Perinat Epidemiol. 2003. Vol. 17, N 1. P. 106–112. doi: 10.1046/j.1365-3016.2003.00460.x
  134. Slattery M.L., Edwards S.L., Caan B.J., et al. Response rates among control subjects in case-control studies//Ann Epidemiol. 1995. Vol. 5, N 3. P. 245–249. doi: 10.1016/1047-2797(94)00113-8
  135. Schulz K.F., Grimes D.A. Case-control studies: research in reverse//Lancet. 2002. Vol. 359, N 9304. P. 431–434. doi: 10.1016/S0140-6736(02)07605-5
  136. Olson S.H., Voigt L.F., Begg C.B., Weiss N.S. Reporting participation in case-control studies//Epidemiology. 2002. Vol. 13, N 2. P. 123–126. doi: 10.1097/00001648-200203000-00004
  137. Morton L.M., Cahill J., Hartge P. Reporting participation in epidemiologic studies: a survey of practice//Am J Epidemiol. 2006. Vol. 163, N 3. P. 197–203. doi: 10.1093/aje/kwj036
  138. Olson S.H. Reported participation in case-control studies: changes over time//Am J Epidemiol. 2001. Vol. 154, N 6. P. 574–581. doi: 10.1093/aje/154.6.574
  139. Sandler D.P. On revealing what we’d rather hide: the problem of describing study participation//Epidemiology. 2002. Vol. 13, N 2. P. 117. doi: 10.1097/00001648-200203000-00001
  140. Hepworth S.J., Schoemaker M.J., Muir K.R., et al. Mobile phone use and risk of glioma in adults: case-control study//BMJ. 2006. Vol. 332, N 7546. P. 883–887. doi: 10.1136/bmj.38720.687975.55
  141. Hay A.D., Wilson A., Fahey T., Peters T.J. The duration of acute cough in pre-school children presenting to primary care: a prospective cohort study//Fam Pract. 2003. Vol. 20, N 6. P. 696–705. doi: 10.1093/fampra/cmg613
  142. Egger M., Juni P., Bartlett C. Value of flow diagrams in reports of randomized controlled trials//JAMA. 2001. Vol. 285, N 15. P. 1996–1999. doi: 10.1001/jama.285.15.1996
  143. Osella A.R., Misciagna G., Guerra V.M., et al. Hepatitis C virus (HCV) infection and liver-related mortality: a population-based cohort study in southern Italy. The Association for the Study of Liver Disease in Puglia//Int J Epidemiol. 2000. Vol. 29, N 5. P. 922–927. doi: 10.1093/ije/29.5.922
  144. Dales L.G., Ury H.K. An improper use of statistical significance testing in studying covariables//Int J Epidemiol. 1978. Vol. 7, N 4. P. 373–375. doi: 10.1093/ije/7.4.373
  145. Maldonado G., Greenland S. Simulation study of confounder-selection strategies//Am J Epidemiol. 1993. Vol. 138, N 11. P. 923–936. doi: 10.1093/oxfordjournals.aje.a116813
  146. Tanis B.C., van den Bosch M.A., Kemmeren J.M., et al. Oral contraceptives and the risk of myocardial infarction//N Engl J Med. 2001. Vol. 345, N 25. P. 1787–1793. doi: 10.1056/NEJMoa003216
  147. Rothman K.J., Greenland S. Precision and Validity in Epidemiologic Studies. In: Rothman KJ, Greenland S, editors. Modern epidemiology. 2nd ed. Lippincott Raven; 1998. Р. 120–125.
  148. Clark T.G., Altman D.G., De Stavola B.L. Quantification of the completeness of follow-up//Lancet. 2002. Vol. 359, N 9314. P. 1309–1310. doi: 10.1016/S0140-6736(02)08272-7
  149. Qiu C., Fratiglioni L., Karp A., et al. Occupational exposure to electromagnetic fields and risk of Alzheimer’s disease//Epidemiology. 2004. Vol. 15, N 6. P. 687–694. doi: 10.1097/01.ede.0000142147.49297.9d
  150. Kengeya-Kayondo J.F., Kamali A., Nunn A.J., et al. Incidence of HIV-1 infection in adults and socio-demographic characteristics of seroconverters in a rural population in Uganda: 1990-1994//Int J Epidemiol. 1996. Vol. 25, N 5. P. 1077–1082. doi: 10.1093/ije/25.5.1077
  151. Mastrangelo G., Fedeli U., Fadda E., et al. Increased risk of hepatocellular carcinoma and liver cirrhosis in vinyl chloride workers: synergistic effect of occupational exposure with alcohol intake//Environ Health Perspect. 2004. Vol. 112, N 11. P. 1188–1192. doi: 10.1289/ehp.6972
  152. Salo P.M., Arbes S.J., Sever M., et al. Exposure to Alternaria alternata in US homes is associated with asthma symptoms//J Allergy Clin Immunol. 2006. Vol. 118, N 4. P. 892–898. doi: 10.1016/j.jaci.2006.07.037
  153. Pocock S.J., Clayton T.C., Altman D.G. Survival plots of time-to-event outcomes in clinical trials: good practice and pitfalls//Lancet. 2002. Vol. 359, N 9318. P. 1686–1689. doi: 10.1016/S0140-6736(02)08594-X
  154. Sasieni P. A note on the presentation of matched case-control data//Stat Med. 1992. Vol. 11, N 5. P. 617–620. doi: 10.1002/sim.4780110506
  155. Lee G.M., Neutra R.R., Hristova L., et al. A nested case-control study of residential and personal magnetic field measures and miscarriages//Epidemiology. 2002. Vol. 13, N 1. P. 21–31. doi: 10.1097/00001648-200201000-00005
  156. Tiihonen J., Walhbeck K., Lonnqvist J., et al. Effectiveness of antipsychotic treatments in a nationwide cohort of patients in community care after first hospitalisation due to schizophrenia and schizoaffective disorder: observational follow-up study//BMJ. 2006. Vol. 333, N 7561. P. 224. doi: 10.1136/bmj.38881.382755.2F
  157. Christenfeld N.J. Sloan R.P., Carroll D., Greenland S. Risk factors, confounding, and the illusion of statistical control//Psychosom Med. 2004. Vol. 66, N 6. P. 868–875. doi: 10.1097/01.psy.0000140008.70959.41
  158. Smith G.D., Phillips A. Declaring independence: why we should be cautious//J Epidemiol Community Health. 1990. Vol. 44, N 4. P. 257–258. doi: 10.1136/jech.44.4.257
  159. Greenland S., Neutra R. Control of confounding in the assessment of medical technology//Int J Epidemiol. 1980. Vol. 9, N 4. P. 361–367. doi: 10.1093/ije/9.4.361
  160. Robins J.M. Data, design, and background knowledge in etiologic inference//Epidemiology. 2001. Vol. 12, N 3. P. 313–320. doi: 10.1097/00001648-200105000-00011
  161. Sagiv S.K., Tolbert P.E., Altshul L.M., Korrick S.A. Organochlorine exposures during pregnancy and infant size at birth//Epidemiology. 2007. Vol. 18, N 1. P. 120–129. doi: 10.1097/01.ede.0000249769.15001.7c
  162. World Health Organization. Body Mass Index (BMI). 2007. Available from: http://www.euro.who.int/nutrition/20030507_1
  163. Beral V. Breast cancer and hormone-replacement therapy in the Million Women Study//Lancet. 2003. Vol. 362, N 9382. P. 419–427. doi: 10.1016/s0140-6736(03)14065-2
  164. Hill A.B. The environment and disease: Association or causation?//Proc R Soc Med. 1965. Vol. 58, N 5. P. 295–300. doi: 10.1177/003591576505800503
  165. Vineis P. Causality in epidemiology//Soz Praventivmed. 2003. Vol. 48, N 2. P. 80–87. doi: 10.1007/s00038-003-1029-7
  166. Empana J.P., Ducimetiere P., Arveiler D., et al. Are the Framingham and PROCAM coronary heart disease risk functions applicable to different European populations? The PRIME Study//Eur Heart J. 2003. Vol. 24, N 21. P. 1903–1911. doi: 10.1016/j.ehj.2003.09.002
  167. Tunstall-Pedoe H., Kuulasmaa K., Mahonen M., et al. Contribution of trends in survival and coronary-event rates to changes in coronary heart disease mortality: 10-year results from 37 WHO MONICA project populations. Monitoring trends and determinants in cardiovascular disease//Lancet. 1999. Vol. 353, N 9164. P. 1547–1557. doi: 10.1016/S0140-6736(99)04021-0
  168. Cambien F., Chretien J.M., Ducimetiere P., et al. Is the relationship between blood pressure and cardiovascular risk dependent on body mass index?//Am J Epidemiol. 1985. Vol. 122, N 3. P. 434–442. doi: 10.1093/oxfordjournals.aje.a114124
  169. Hosmer D.W., Taber S., Lemeshow S. The importance of assessing the fit of logistic regression models: a case study//Am J Public Health. 1991. Vol. 81, N 12. P. 1630–1635. doi: 10.2105/AJPH.81.12.1630
  170. Tibshirani R. A plain man’s guide to the proportional hazards model//Clin Invest Med. 1982. Vol. 5, N 1. P. 63–68.
  171. Rockhill B., Newman B., Weinberg C . Use and misuse of population attributable fractions//Am J Public Health. 1998. Vol. 88, N 1. P. 15–19. doi: 10.2105/AJPH.88.1.15
  172. Uter W., Pfahlberg A. The application of methods to quantify attributable risk in medical practice//Stat Methods Med Res. 2001. Vol. 10, N 3. P. 231–237. doi: 10.1177/096228020101000305
  173. Schwartz L.M., Woloshin S., Dvorin E.L., Welch H.G. Ratio measures in leading medical journals: structured review of accessibility of underlying absolute risks//BMJ. 2006. Vol. 333, N 7581. P. 1248. doi: 10.1136/bmj.38985.564317.7C
  174. Nakayama T., Zaman M.M., Tanaka H. Reporting of attributable and relative risks, 1966-97//Lancet. 1998. Vol. 351, N 9110. P. 1179. doi: 10.1016/S0140-6736(05)79123-6
  175. Cornfield J. A method of estimating comparative rates from clinical data; applications to cancer of the lung, breast, and cervix//J Natl Cancer Ins. 1951. Vol. 11, N 6. P. 1269–1275.
  176. Pearce N. What does the odds ratio estimate in a case-control study?//Int J Epidemiol. 1993. Vol. 22, N 6. P. 1189–1192. doi: 10.1093/ije/22.6.1189
  177. Rothman K.J., Greenland S., Rothman K.J., Greenland S. Measures of Disease Frequency. Modern epidemiology. 2nd ed. Lippincott Raven, 1998. Р. 44–45.
  178. Doll R., Hill A.B. The mortality of doctors in relation to their smoking habits: a preliminary report.//BMJ. 1954. Vol. 1, N 4877. P. 1451–1455. doi: 10.1136/bmj.1.4877.1451
  179. Ezzati M., Lopez A.D. Estimates of global mortality attributable to smoking in 2000//Lancet. 2003. Vol. 362, N 9387. P. 847–852. doi: 10.1016/S0140-6736(03)14338-3
  180. Greenland S. Applications of Stratified Analysis Methods. In: Rothman KJ, Greenland S, editors. Modern epidemiology. 2nd ed. Lippincott Raven, 1998. Р. 295–297.
  181. Rose G. Sick individuals and sick populations//Int J Epidemiol. 2001. Vol. 30, N 3. P. 427–432. discussion. doi: 10.1093/ije/30.3.427
  182. Vandenbroucke J.P., Koster T., Briet E., et al. Increased risk of venous thrombosis in oral-contraceptive users who are carriers of factor V Leiden mutation//Lancet. 1994. Vol. 344, N 8935. P. 1453–1457. doi: 10.1016/S0140-6736(94)90286-0
  183. Botto L.D., Khoury M.J. Commentary: facing the challenge of gene-environment interaction: the two-by-four table and beyond//Am J Epidemiol. 2001. Vol. 153, N 10. P. 1016–1020. doi: 10.1093/aje/153.10.1016
  184. Wei L., MacDonald T.M., Walker B.R. Taking glucocorticoids by prescription is associated with subsequent cardiovascular disease//Ann Intern Med. 2004. Vol. 141, N 10. P. 764–770. doi: 10.7326/0003-4819-141-10-200411160-00007
  185. Martinelli I., Taioli E., Battaglioli T., et al. Risk of venous thromboembolism after air travel: interaction with thrombophilia and oral contraceptives//Arch Intern Med. 2003. Vol. 163, N 22. P. 2771–2774. doi: 10.1001/archinte.163.22.2771
  186. Kyzas P.A., Loizou K.T., Ioannidis J.P. Selective reporting biases in cancer prognostic factor studies//J Natl Cancer Inst. 2005. Vol. 97, N 14. P. 1043–1055. doi: 10.1093/jnci/dji184
  187. Rothman K.J., Greenland S., Walker A.M. Concepts of interaction//Am J Epidemiol. 1980. Vol. 112, N 4. P. 467–470. doi: 10.1093/oxfordjournals.aje.a113015
  188. Saracci R. Interaction and synergism//Am J Epidemiol. 1980. Vol. 112, N 4. P. 465–466. doi: 10.1093/oxfordjournals.aje.a113014
  189. Rothman K.J. Epidemiology. An introduction. Oxford: Oxford University Press, 2002. Р. 168–180.
  190. Rothman K.J. Interactions Between Causes. Modern epidemiology. Boston: Little Brown, 1986. Р. 311–326.
  191. Hess D.R. How to write an effective discussion//Respir Care. 2004. Vol. 49, N 10. P. 1238–1241.
  192. Horton R. The hidden research paper//JAMA .2002. Vol. 287, N 21. P. 2775–2778. doi: 10.1001/jama.287.21.2775
  193. Horton R. The rhetoric of research//BMJ. 1995. Vol. 310, N 6985. P. 985–987. doi: 10.1136/bmj.310.6985.985
  194. Docherty M., Smith R. The case for structuring the discussion of scientific papers//BMJ. 1999. Vol. 318, N 7193. P. 1224–1225. doi: 10.1136/bmj.318.7193.1224
  195. Perneger T.V., Hudelson P.M. Writing a research article: advice to beginners//Int J Qual Health Care. 2004. Vol. 16, N 3. P. 191–192. doi: 10.1093/intqhc/mzh053
  196. Annals of Internal Medicine. Information for authors. Available from: http://www.annals.org/shared/author_info.html. Accessed 10 September 2007.
  197. Maldonado G., Poole C. More research is needed//Ann Epidemiol. 1999. Vol. 9, N 1. P. 17–18. doi: 10.1016/s1047-2797(98)00050-7
  198. Phillips C.V. The economics of ‘more research is needed’//Int J Epidemiol. 2001. Vol. 30, N 4. P. 771–776. doi: 10.1093/ije/30.4.771
  199. Winkleby M.A., Kraemer H.C., Ahn D.K., Varady A.N. Ethnic and socioeconomic differences in cardiovascular disease risk factors: findings for women from the Third National Health and Nutrition Examination Survey, 1988–1994//JAMA. 1998. Vol. 280, N 4. P. 356–362. doi: 10.1001/jama.280.4.356
  200. Galuska D.A., Will J.C., Serdula M.K., Ford E.S. Are health care professionals advising obese patients to lose weight?//JAMA. 1999. Vol. 282, N 16. P. 1576–1578. doi: 10.1001/jama.282.16.1576
  201. Spearman C. The proof and measurement of association between two things//Am J Psychol. 1904. Vol. 15, N 1. P. 72–101. doi: 10.2307/1412159
  202. Fuller W.A., Hidiroglou M.A. Regression estimates after correcting for attenuation//J Am Stat Assoc. 1978. Vol. 73, N 361. P. 99–104. doi: 10.1080/01621459.1978.10480011
  203. MacMahon S., Peto R., Cutler J., et al. Blood pressure, stroke, and coronary heart disease. Part 1, Prolonged differences in blood pressure: prospective observational studies corrected for the regression dilution bias//Lancet. 1990. Vol. 335, N 8692. P. 765–774. doi: 10.1016/0140-6736(90)90878-9
  204. Phillips A.N., Smith G.D. How independent are “independent” effects? Relative risk estimation when correlated exposures are measured imprecisely//J Clin Epidemiol. 1991. Vol. 44, N 11. P. 1223–1231. doi: 10.1016/0895-4356(91)90155-3
  205. Phillips A.N. Smith G.D. Bias in relative odds estimation owing to imprecise measurement of correlated exposures//Stat Med. 1992. Vol. 11, N 7. P. 953–961. doi: 10.1002/sim.4780110712
  206. Greenland S. The effect of misclassification in the presence of covariates//Am J Epidemiol. 1980. Vol. 112, N 4. P. 564–569. doi: 10.1093/oxfordjournals.aje.a113025
  207. Poole C., Peters U., Il’yasova D., Arab L. Commentary: This study failed?//Int J Epidemiol. 2003. Vol. 32, N 4. P. 534–535. doi: 10.1093/ije/dyg197
  208. Kaufman J.S., Cooper R.S., McGee D.L. Socioeconomic status and health in blacks and whites: the problem of residual confounding and the resiliency of race//Epidemiology. 1997. Vol. 8, N 6. P. 621–628. doi: 10.1097/00001648-199710000-00002
  209. Greenland S. Randomization, statistics, and causal inference//Epidemiology. 1990. Vol. 1, N 6. P. 421–429. doi: 10.1097/00001648-199011000-00003
  210. Taubes G. Epidemiology faces its limits//Science. 1995. Vol. 269, N 5221. P. 164–169. doi: 10.1126/science.7618077
  211. Temple R. Meta-analysis and epidemiologic studies in drug development and postmarketing surveillance//JAMA. 1999. Vol. 281, N 9. P. 841–844. doi: 10.1001/jama.281.9.841
  212. Greenberg R.S., Shuster J.L. Epidemiology of cancer in children//Epidemiol Rev. 1985. Vol. 7. P. 22–48. doi: 10.1093/oxfordjournals.epirev.a036284
  213. Kushi L.H., Mink P.J., Folsom A.R., et al. Prospective study of diet and ovarian cancer//Am J Epidemiol. 1999. Vol. 149, N 1. P. 21–31. doi: 10.1093/oxfordjournals.aje.a009723
  214. Kemmeren J.M., Algra A., Meijers J.C., et al. Effect of second- and third-generation oral contraceptives on the protein C system in the absence or presence of the factor V Leiden mutation: a randomized trial//Blood. 2004. Vol. 103, N 3. P. 927–933. doi: 10.1182/blood-2003-04-1285
  215. Egger M., May M., Chene G., et al. Prognosis of HIV-1-infected patients starting highly active antiretroviral therapy: a collaborative analysis of prospective studies//Lancet. 2002. Vol. 360, N 9327. P. 119–129. doi: 10.1016/S0140-6736(02)09411-4
  216. Campbell D.T. Factors relevant to the validity of experiments in social settings//Psychol Bull. 1957. Vol. 54, N 4. P. 297–312. doi: 10.1037/h0040950
  217. Justice A.C., Covinsky K.E., Berlin J.A. Assessing the generalizability of prognostic information//Ann Intern Med. 1999. Vol. 130, N 6. P. 515–524. doi: 10.7326/0003-4819-130-6-199903160-00016
  218. Krimsky S., Rothenberg L.S. Conflict of interest policies in science and medical journals: editorial practices and author disclosures//Sci Eng Ethics. 2001. Vol. 7, N 2. P. 205–218. doi: 10.1007/s11948-001-0041-7
  219. Bekelman J.E., Li Y., Gross C. Scope and impact of financial conflicts of interest in biomedical research: a systematic review//JAMA. 2003. Vol. 289, N 4. P. 454–465. doi: 10.1001/jama.289.4.454
  220. Davidson R.A. Source of funding and outcome of clinical trials//J Gen Intern Med. 1986. Vol. 1, N 3. P. 155–158. doi: 10.1007/BF02602327
  221. Stelfox H.T., Chua G., O’Rourke K., Detsky A.S. Conflict of interest in the debate over calcium-channel antagonists//N Engl J Med. 1998. Vol. 338, N 2. P. 101–106. doi: 10.1056/NEJM199801083380206
  222. Lexchin J., Bero L.A., Djulbegovic B., Clark O. Pharmaceutical industry sponsorship and research outcome and quality: systematic review//BMJ. 2003. Vol. 326, N 7400. P. 1167–1170. doi: 10.1136/bmj.326.7400.1167
  223. Als-Nielsen B., Chen W., Gluud C., Kjaergard L.L. Association of funding and conclusions in randomized drug trials: a reflection of treatment effect or adverse events?//JAMA. 2003. Vol. 290, N 7. P. 921–928. doi: 10.1001/jama.290.7.921
  224. Barnes D.E., Bero L.A. Why re s on the health effects of passive smoking reach different conclusions//JAMA. 1998. Vol. 279, N 19. P. 1566–1570. doi: 10.1001/jama.279.19.1566
  225. Barnes D.E., Bero L.A. Industry-funded research and conflict of interest: an analysis of research sponsored by the tobacco industry through the Center for Indoor Air Research//J Health Polit Policy Law. 1996. Vol. 21, N 3. P. 515–542. doi: 10.1215/03616878-21-3-515
  226. Glantz S.A., Barnes D.E., Bero L., et al. Looking through a keyhole at the tobacco industry. The Brown and Williamson documents//JAMA. 1995. Vol. 274, N 3. P. 219–224. doi: 10.1001/jama.1995.03530030039032
  227. Huss A., Egger M., Hug K., et al. Source of funding and results of studies of health effects of mobile phone use: systematic review of experimental studies//Environ Health Perspect. 2007. Vol. 115, N 1. P. 1–4. doi: 10.1289/ehp.9149
  228. Safer D.J. Design and reporting modifications in industry-sponsored comparative psychopharmacology trials//J Nerv Ment Dis. 2002. Vol. 190, N 9. P. 583–592. doi: 10.1097/00005053-200209000-00002
  229. Aspinall R.L., Goodman N.W. Denial of effective treatment and poor quality of clinical information in placebo controlled trials of ondansetron for postoperative nausea and vomiting: a review of published trials//BMJ. 1995. Vol. 311, N 7009. P. 844–846. doi: 10.1136/bmj.311.7009.844
  230. Chan A.W., Hrobjartsson A., Haahr M.T., et al. Empirical evidence for selective reporting of outcomes in randomized trials: comparison of protocols to published articles//JAMA. 2004. Vol. 291, N 20. P. 2457–2465. doi: 10.1001/jama.291.20.2457
  231. Melander H., Ahlqvist-Rastad J., Meijer G., Beermann B. Evidence b(i)ased medicine-selective reporting from studies sponsored by pharmaceutical industry: review of studies in new drug applications//BMJ. 2003. Vol. 326, N 7400. P. 1171–1173. doi: 10.1136/bmj.326.7400.1171
  232. Scherer R.W., Langenberg P., von Elm E. Full publication of results initially presented in abstracts. Cochrane Database of Systematic Reviews. (Issue 2). Art. No.: MR000005. Available from: http://www.cochrane.org/reviews/en/mr000005.html. Accessed 10 September 2005. doi: 10.1002/14651858.MR000005.pub2
  233. Moher D., Schulz K.F., Altman D.G. The CONSORT statement: revised recommendations for improving the quality of reports of parallel-group randomised trials//Lancet. 2001. Vol. 357, N 9263. P. 1191–1194. doi: 10.1016/S0140-6736(00)04337-3
  234. Stroup D.F., Berlin J.A., Morton S.C., et al. Meta-analysis of observational studies in epidemiology: a proposal for reporting. Meta-analysis Of Observational Studies in Epidemiology (MOOSE) group//JAMA. 2000. Vol. 283, N 15. P. 2008–2012. doi: 10.1001/jama.283.15.2008
  235. Altman D.G., Schulz K.F., Moher D., et al. The revised CONSORT statement for reporting randomized trials: explanation and elaboration//Ann Intern Med. 2001. Vol. 134, N 8. P. 663–694. doi: 10.7326/0003-4819-134-8-200104170-00012
  236. Moher D. CONSORT: an evolving tool to help improve the quality of reports of randomized controlled trials. Consolidated Standards of Reporting Trials//JAMA. 1998. Vol. 279, N 18. P. 1489–1491. doi: 10.1001/jama.279.18.1489
  237. Begg C., Cho M., Eastwood S., et al. Improving the quality of reporting of randomized controlled trials. The CONSORT statement//JAMA. 1996. Vol. 276, N 8. P. 637–639. doi: 10.1001/jama.276.8.637.

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