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Beware of Registries for their Biases

Beware of Registries for their Biases. Hasan Yazici University of Istanbul. Disclosures. Pfizer (Turkey) – travel support & speaker’s fees Merck (Turkey) – travel support & speaker’s fees. Beware of Observational Studies based on Registries for their Biases. Hasan Yazici

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Beware of Registries for their Biases

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  1. Beware of RegistriesfortheirBiases Hasan Yazici University of Istanbul

  2. Disclosures • Pfizer (Turkey) – travel support & speaker’s fees • Merck (Turkey) – travel support & speaker’s fees

  3. Beware of ObservationalStudiesbased on RegistriesfortheirBiases Hasan Yazici University of Istanbul

  4. Plan • Forandagainstobservationalstudies • Fewhistoricalnotes • A summary of importantbiases in observationalstudiesbased on registriesandadministrative data bases • Thebias of determiningcancerincidence in registries - a recentexample • Somenaivearithmetic • Whatto do? • Inbrief

  5. Observational StudiesAdvantages • Real life data • Relatively cheap • Potential to observe multiple outcomes • Ability to assess cause – effect relations • Long term observations

  6. Observational StudiesProblems • Many are cross sectional or retrospective. • Selection bias including completeness of recruitment • Confounders • Uniformity of assessment • Control groups

  7. RCTs vs Observationalstudies • Efficacy : RCT superior • Harm: Observationalstudysuperior • Biomarkers: Observationalstudysuperior JP Vandenbroucke BMJ, 2011

  8. RCTs vs Observationalstudies • Efficacy : RCT superior? • Harm: Observationalstudysuperior • Biomarkers: Observationalstudysuperior JP Vandenbroucke BMJ, 2011

  9. The DES* Drama • DES began to be used for threatened abortion (1949) • Efficacy could not be shown in a double blind, placebo controlled study at University of Chicago (1958) • An “epidemic” of vaginal cancer among girls in Boston (1971) • Among 8 patients with vaginal cancer 7 were daughters of mothers who had used DES during pregnancy. This contrasted with mothers of 32 healthy girls (born in the same hospital within a day or two) among whom there were no DES users. * diethylstilbestrol

  10. The DES* Drama • DES beganto be usedforthreatenedabortion (1949) • Efficacycould not be shown in a doubleblind, placebocontrolledstudy at University of Chicago (1958) • An “Epidemic” of vaginalcanceramonggirls in Boston (1971) • Among 8 patientswithvaginalcancer 7 weredaughters of motherswho had used DES duringpregnancy. Thiscontrastedwithmothers of 32 healthygirls (born in thesamehospitalwithin a dayortwo) amongwhomtherewereno DES users. • FDA banned DES in pregnancy (1971). • A study (Mayo Clinic) in mid 70’s among 800 youngwomenwith a motherwho had used DES duringpregnancydid not revealanycases of vaginalcancer. • No surprise. Since frequency of vaginalcancer: <1/1000 users. • A furthercasecontrolstudyfrom NY StateTumorRegistryconfirmedtheassociation. * diethylstilbestrol

  11. The Estrone Drama • “Like a gallant knight (the author of Feminine Forever) has come to rescue his fair lady not at the time of her bloom and flowering but in her desparing years; at a time of life when the preservation and prolongation of her femaleness are so paramount…By throwing down his gauntlet, he challanges the reluctant physician to follow him in providing the hormones that may allow for a smoother transition to the menopausal years ahead. Women will be emancipated only when the shackles of hormonal deprevation are loosed.” in Investigating Disease Patterns, Stolley&Lasky, 1995

  12. in Investigating Disease Patterns, Stolley&Lasky, 1995

  13. ....I think this is rather misleading. Of the 26 lymphomas they refer to in the main text, 14 occurred within 2 months of TNF antagonist use. Thus, a more realistic comparator would be a deduced (from the annual rates) 2-month incidence of lymphoma in the general population.... H Yazici Arthritis Rheum 2003

  14. Time to Neoplasia Based on T Bongartz et al. JAMA 2006

  15. The Wandering Comparison of Risk(Lymphoma) M. Hudson & S. Suissa Arthritis Care and Res, 2010

  16. The Wandering Comparison of Risk(Lymphoma) M. Hudson & S. Suissa Arthritis Care and Res, 2010

  17. The Wandering Comparison of Risk (Infections)

  18. The Wandering Comparison of Risk (Infections)

  19. Channeling Bias(in an administrative data base)

  20. Channeling Bias(in an administrative data base)

  21. Channeling Bias(in an administrative data base)

  22. The Immortal Time Bias • ..arises in a cohort study where an outcome can hinder, totally or partially, the realization of the exposure.

  23. The Immortal Time Bias • Hydroxychloroquine decreases cancer in SLE by 85% • G. Ruiz Irastorza et al. Ann Rheum Dis, 2007 • Statins decrease lung cancer by 45%. • V. Khuarana et al. Chest, 2007 • LE Levesque et al. Br Med J, 2010

  24. References • Eur Respir J (4) • Arch Intern Med (2) • Am J Med (2) • Am J Respir Crit Care Med (2) • Lancet (2) • JAMA (1) • Am J Respir Med (1) • J Allergy Clinical Immunol (1) • Ann Allergy Asthma Immunol (1) • Thorax (1) • Pediatrics (1) • Ann Pharmacother(1) • Diabet Med (1)

  25. Misclassified Immortal Time • Theauthorsstudy a completeregistry of SLE patientsbetween 2 time points. • Theexposedgroupconsists of patientswho had ever usedhydroxychlorquine. • Thenon – exposedgroupconsists of patientswhohaveneverusedhydroxychloroquine. • Theauthorsfindsignificantlylesscancers in the “exposed = ever used” group.

  26. OR for death = Odds of death in the exposed Odds of death in the non-exposed

  27. What is wrong? • In the numerator those patients who had died due to malignancy could not have been prescribed hydroxychloroqine. • Thus the duration of follow up time that can lead to malignancy in the numerator is actually shorter and this decreases the odds for a malignancy in the numerator making it lower than what is said.

  28. The RDPR Study • Wehypothesizethattopicalantifungals (TA) decreasemortality. • IntheRegistryvilleDrugPrescriptionsRegistry (RDPR) betweenJanuary 1, 2009 andending on March 31st, 2009 weidentify 1000 patientswith an ever prescriptionfor TA. • Wefollowallpatientsfomthe time of prescriptiontoDecember 31st 2010, foremergingdeath. • Weusethe RMR (RegistryvilleMortalityRegistry) toconfirmthedeaths. • From RDPR wealsorandomize a 1000 sample of age, genderandpracticallyeverything else matchedindividuals AND alsofollowthemforthesameoutcomeuptoDecember 31st. 2010. • Exposedgroup: patientswith a prescriptionfor a TA • Non- exposedgroup: patientswithotherprescriptions • Outcome: death

  29. The RDPR Study At theend of thestudywecompare: OR (exposed)/OR (non-exposed) 30 people (30/732 pt. yrs.) in theexposedgroup; 60 people (60/950 pt. yrs.) in thenon-exposedgrouphavedies. TA significantlylessensmortality OR=0.50; p= 0.009

  30. Excluded Immortal Time • Wecorrectlyexcludefromthenumeratorthefollowup of thosepatientsbeforetheywereprescribedtheexposuredrug. This is theimmortal time and, again, deaths can onlyhappenaftertheexposure (theprescription).

  31. Excluded Immortal Time • Wecorrectlyexcludefromthenumeratorthefollowup of thosepatientsbeforetheywereprescribedtheexposuredrug. This is theimmortal time and, again, deaths can onlyhappenaftertheexposure (theprescription). • Howeverthis is not enough. This time periodshould be addedtothedenominator.

  32. Exposed

  33. Exposed Entry

  34. Exposed Entry Calendar Age Birth date Disease onset Diagnosis Registration in a clinic Registration in a database

  35. Exposed Exposure ie prescription Entry Calendar Age Birth date Disease onset Diagnosis Registration in a clinic Registration in a database

  36. Exposed Exposure ie prescription Observation ends Entry Calendar Age Birth date Disease onset Diagnosis Registration in a clinic Registration in a database

  37. Exposed Unexposed Exposure ie prescription Observation ends Entry Calendar Age Birth date Disease onset Diagnosis Registration in a clinic Registration in a database

  38. ExposedUnexposed Exposure ie prescription Observation ends Entry Calendar Age Birth date Disease onset Diagnosis Registration in a clinic Registration in a database Observation ends Entry

  39. Exposed Unexposed Exposure ie prescription Observation ends Entry immortal time Calendar Age Birth date Disease onset Diagnosis Registration in a clinic Registration in a database Observation ends Entry

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