USING EVIDENCE FOR HEMATOLOGY LABORATORY PRACTICE. Alfonso Iorio McMaster University, Canada

Transcription

1 USING EVIDENCE FOR HEMATOLOGY LABORATORY PRACTICE Alfonso Iorio McMaster University, Canada

2 Disclosures Financial No relevant rela1onships to disclose Research funding in the field of hemophilia care Intellectual Faculty at McMaster University Chief of the Health Informa1on Research Unit Member of the GRADE working group

3 Our i1nerary Random reflec1ons on laboratory evidence: Evidence Genera1on Players Study designs Evidence Search and synthesis Issuing clinical prac1ce recommenda1ons

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5 Evidence EVIDENCE & HEMATOLOGY LABORATORY PRACTICE (Confidence in the) answer to a relevant ques1on Laboratory medicine Measurement(s) providing answer to ques1ons of Diagnosis (screening or confirma1on) Treatment (monitoring or treatment response) Prognosis (diagnosis of a risk condi1on)

6 Ques1ons in EBM [P]opula1on In pa1ents without bleeding history [I]nterven1on Does a normal PTT result [C]omparator.(within the normal range) [O]utcome Rule out a bleeding disorder [T]ime Before ENT surgery

7 Ques1ons in EBM [P]opula1on In pa1ents without bleeding history [I]nterven1on Can a POC PTT be used [C]omparator instead that a standard PTT [O]utcome To rule out a bleeding disorder [T]ime Before ENT surgery

8 Perspec1ves.. Is there a purely laboratory domain? Normal ranges Test valida1on Test characteris1cs Diagnos1c algorithms Pre- analy1cal variables

9 Perspec1ves.. Is there a purely clinical domain? Treatment? Well Evidence based treatment is defined in PICO terms P and O have in a vast majority of cases a laboratory component (in hematology more than average).

10 Perspec1ves.. Evidence is generated by a close interac1on of laboratory and clinical medicine therefore Evidence based clinical prac1ce in both fields would require both components in most cases

11 One simple example: D- Dimer to predict recurrent VTE Douke1s J, Iorio A. Pa1ent- Level Meta- analysis: Effect of Measurement Timing, Threshold, and PaSent Age on Ability of D- Dimer Tes1ng to Assess 1. Douke1s J, Iorio A. Pa1ent- Level Meta- analysis: Effect of Measurement Timing, Threshold, and Pa1ent Age on Ability of D- Dimer Tes1ng to Assess Recurrence Risk Acer Unprovoked Venous Thromboembolism. Ann Intern Med 2010;153: Baglin T, Iorio A. Does the clinical presenta1on and extent of venous thrombosis predict likelihood and type of recurrence? A pa1ent level meta- analysis. J Thromb Haemost 2010;8: Douke1s J,.Iorio A. Risk of recurrence acer venous thromboembolism in men and women: pa1ent level meta- analysis. BMJ 2011;342:d Toselo A, Iorio A, et al. Predic1ng disease recurrence in pa1ents with previous unprovoked venous thromboembolism: a proposed predic1on score (DASH). J Thromb Haemost 2012;10: Marcucci M, Iorio A. Pa1ent- level compared with study- level meta- analyses demonstrate consistency of D- dimer as predictor of venous thromboembolic recurrences. J Clin Epidemiol 2013;66: Marcucci M, Iorio A, et al. Management of pa1ents with unprovoked venous thromboembolism: an evidence- based and prac1cal approach. Curr Treat Op>ons Cardiovasc Med 2013;15: Iorio A, Douke1s JD. Ruling out DVT using the Wells rule and a D- dimer test. BMJ 2014;348:g1637 g Marcucci M, Iorio A, et al. Risk of recurrence acer a first unprovoked venous thromboembolism: external valida1on of the Vienna Predic1on Model with pooled individual pa1ent data. J Thromb Haemost 2015;13: Recurrence Risk Acer Unprovoked Venous Thromboembolism. Ann Intern Med 2010;153:

12 Cut point 500 vs 250 Age =< 65 vs > 65 Tes1ng <3, vs 3-5 vs >5 weeks

13 One simple example: D- Dimer to predict recurrent VTE 1. Douke1s J, Iorio A. Pa1ent- Level Meta- analysis: Effect of Measurement Timing, Threshold, and Pa1ent Age on Ability of D- Dimer Tes1ng to Assess Recurrence Risk Acer Unprovoked Venous Thromboembolism. Ann Intern Med 2010;153: Baglin T, Iorio A. Does the clinical presenta1on and extent of venous thrombosis predict likelihood and type of recurrence? A pa1ent level meta- analysis. J Thromb Haemost 2010;8: Douke1s J,.Iorio A. Risk of recurrence acer venous thromboembolism in men and women: pa1ent level meta- analysis. BMJ 2011;342:d Toselo A, Iorio A, et al. Predic1ng disease recurrence in pa1ents with previous unprovoked venous thromboembolism: a proposed predic1on score (DASH). J Thromb Haemost 2012;10: Marcucci M, Iorio A. Pa1ent- level compared with study- level meta- analyses demonstrate consistency of D- dimer as predictor of venous thromboembolic recurrences. J Clin Epidemiol 2013;66: Marcucci M, Iorio A, et al. Management of pa1ents with unprovoked venous thromboembolism: an evidence- based and prac1cal approach. Curr Treat Op>ons Cardiovasc Med 2013;15: Iorio A, Douke1s JD. Ruling out DVT using the Wells rule and a D- dimer test. BMJ 2014;348:g1637 g Marcucci M, Iorio A, et al. Risk of recurrence acer a first unprovoked venous thromboembolism: external valida1on of the Vienna Predic1on Model with pooled individual pa1ent data. J Thromb Haemost 2015;13: Toselo A, Iorio A, et al. Predic1ng disease recurrence in pa1ents with previous unprovoked venous thromboembolism: a proposed predicson score (DASH). J Thromb Haemost 2012;10: Marcucci M, Iorio A, et al. Risk of recurrence acer a first unprovoked venous thromboembolism: external validason of the Vienna PredicSon Model with pooled individual pa1ent data. J Thromb Haemost 2015;13: Marcucci M, Iorio A. PaSent- level compared with study- level meta- analyses demonstrate consistency of D- dimer as predictor of venous thromboembolic recurrences. J Clin Epidemiol 2013;66:

14 Diagnosis versus Prognosis Test Observa1on Health status (+) (- ) (+A) (- ) (+) (- ) 0 Time n

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16 Phases of diagnos1c studies Phase I Do test results in pa1ent with the target disorders differ from those in normal people? Phase II Are pa1ents with certain test results more likely to have the target results? Phase III Does the test result dis1nguish pa1ents with and without the target disorders among pa1ents in whom it is clinically reasonable ro suspect that the disease is present? Phase IV Do pa1ents who undergo this diagnos1c test fare beler (in their ul1mate health outcomes) than similar pa1ents who are not tested?

17 Diagnos1c test performance indexes Accuracy Sens, Spec, PPV, NPV, Likelihood ra1o Agreement ROC/AUC Misclassifica1on (Re)classifica1on index TP, TN, FP, FN & undetermined

18 Study designs Diagnos1c test (deriva1on valida1on) Diagnos1c algorithm (deriva1on valida1on) Screening procedure (deriva1on valida1on) Incep1on cohort Gold standard Blinding Implementa1on study New test Faster Cheaper Less invasive, safer New test role Triage test Replacement test Add-on test

19 Discrepant analysis Two-test reference standard Latent class analysis Construct validation

20 Bias in Diagnostics Research Inappropriate reference standard Spectrum bias Verification (work-up) bias Partial verification bias Differential verification bias Review bias (lack of blinding) Incorporation bias Bias due to exclusions, indetermined results, etc

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22 Comparison of two tests Bland JM, Altman DG. Sta>s>cal methods for assessing agreement between two methods of clinical measurement. Lancet 1986;1: Bland JM, Altman DG. Comparing methods of measurement: why plofng difference against standard 1 method is misleading. Lancet 1995;346: Bland JM, Altman DG. Applying the right sta>s>cs: analyses of measurement studies. Ultrasound Obstet Gynecol 2003;22:85 93.

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24 The original example Bland JM, Altman DG. Lancet 1986;1:

25 Fancier sta1s1cs Bland JM, Altman DG. Ultrasound Obstet Gynecol 2003;22:85 93.

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27 Graf L, et al. Int J Lab Hematol 2014;36: Bland & Altman plots

28 Graf L, et al. Int J Lab Hematol 2014;36: Bland & Altman plots

29 Classifica1on proper1es Graf L, et al. Int J Lab Hematol 2014;36:

30 SEARCHING AND SUMMARIZING THE EVIDENCE

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33 Systema1c Review in diagnosis SROC Walter SD. Proper1es of the summary receiver opera1ng characteris1c (SROC) curve for diagnos1c test data. Stat Med 2002;21: Harbord RM, Deeks JJ, Egger M, et al. A unifica1on of models for meta- analysis of diagnos1c accuracy studies. Biosta1s1cs 2007;8: Cochrane 64 1tles Rapid diagnos1c tests versus clinical diagnosis for managing fever in seungs where malaria is common Odaga J et al. Cochrane Database of Systema1c Reviews 2014, Issue 4. Art. No.: CD

34 Systema1c review in laboratory hematology 1. Gore CJ, Hopkins WG, Burge CM. Errors of measurement for blood volume parameters: a meta- analysis. J Appl Physiol 2005;99: Wang Y- H, Fan L, Xu W, et al. Detec1on methods of ZAP- 70 in chronic lymphocy1c leukemia. Clin Exp Med 2012;12: Zhi M, Ding EL, Theisen- Toupal J, et al. The landscape of inappropriate laboratory tes1ng: A 15- year meta- analysis. PLoS One 2013;8: Cao C, Liu S, Lou SF, et al. The +252A/G polymorphism in the lymphotoxin- α gene and the risk of non- Hodgkin lymphoma: A meta- analysis. Eur Rev Med Pharmacol Sci 2014;18: Jiang D, Hong Q, Shen Y, et al. The diagnos1c value of DNA methyla1on in leukemia: A systema1c review and meta- analysis. PLoS One 2014;9: Benner A, Mansouri L, Rossi D, et al. MDM2 promotor polymorphism and disease characteris1cs in chronic lymphocy1c leukemia: Results of an individual pa1ent data- based meta- analysis. Haematologica 2014;99: Wang Z, Jia M, Zhao H, et al. Prognos1c impact of pretransplanta1on hyperferri1nemia in adults undergoing allogeneic hematopoie1c SCT: a meta- analysis. Bone Marrow Transplant 2014;49: Nijsten J, Boonacker CWB, Haas M De, et al. Clinical and laboratory predictors of chronic immune thrombocytopenia in children : a systema1c review and meta- analysis. Blood 2015;124:

35 CLINICAL PRACTICE GUIDELINES

36 Guideline in laboratory hematology Area Number Year Pre- analy1c process Cellular analysis, including smears General hematology lab Coagula1on Flow cytometry Hemopathology Hemoglobinopha1es Point- of- care Hayward CPM, Moffat KA, George TI, et al. Assembly and evalua1on of an inventory of guidelines that are available to support clinical hematology laboratory prac1ce. Int J Lab Hematol 2015;x:1 10. doi: /ijlh.12348

37 Guideline in laboratory hematology Area Number Year Pre- analy1c process 0/ Cellular analysis, including smears 3/ General hematology lab 2/ Coagula1on 9/ Flow cytometry 1/ Hemopathology 3/ Hemoglobinopha1es 1/ Point- of- care 0/ Hayward CPM, Moffat KA, George TI, et al. Assembly and evalua1on of an inventory of guidelines that are available to support clinical hematology laboratory prac1ce. Int J Lab Hematol 2015;x:1 10. doi: /ijlh.12348

38 Vlayen J et al. Int J Qual Heal Care 2005;17:

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40 AGREE appraisals

41 6 domains & 23 items Scope & purpose Stakeholder involvement Rigour of development Clarity & presentason Applicability Editorial independence

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44 GRADE FOR DIAGNOSIS (AND PROGNOSIS)

45 BMJ 2008;336: Brozek JL, et al. Allergy Eur J Allergy Clin Immunol 2009;64: Mustafa R et al. J Clin Epidemiol 2013;66: Hu J et al. Implementa1on Science 2011:6:62

46 Study designs IV Old test(s) Randomised Trial or Observational Study Target population New test(s) Are there studies that directly focus on: mortality, morbidity, symptoms, and/or quality of life? TP + FP FN + TN TP + FP FN + TN No Management depending on results Management depending on results Management depending on results Management depending on results Y e s Patient-important outcomes Patient-important outcomes Apply GRADE approach as for treatment or other intervention Schunemann et al. BMJ, 2008

47 Study designs III Accuracy Study Target population Look for diagnostic test accuracy studies New test(s) + Reference test TP FP FN TN Assumptions or indirect evidence about management of patients correctly or incorrectly classified as positive or negative with the new or old test(s) Judgements about patient-important outcomes with a new test and a reference test And then draw inferences from other evidence Schunemann et al. BMJ, 2008

48 GRADE s specifics for diagnosis Review TP,TN, FP,FN Consider indeterminate results Review a spectrum of candidate popula1ons with different disease prevalence Define thresholds to treat and stop tes1ng Consider clinical consequences of the possible results

49 Diagnos1c studies (Preferably from SR) Studies that link (TP, FP, TN, FN) to pa1ent- important outcomes: (Preferably from a SR) GRADE GRADE QoE Diagnos1c test accuracy QoE Linked evidence Balance all outcomes together RecommendaSon

50 Question/Problem Test accuracy Benefits and harms Quality of evidence Values Resources Equity Acceptability Feasibility Recommendation Implementation vidence to decision E

51 P I C O True positives False negatives True negatives False positives Critical? Critical? Important? Not 1. Risk of bias 2. Inconsistency 3. Indirectness 4. Imprecision 5. Publication bias 1. Large effect 2. Dose response 3. Opposing bias & Confounders Quality of evidence & estimates for TP, FN, TN & FP Grade down Grade up? Treatment (side) effects Natural history Confidence in link? Resources Side effects of test Inconclusive results High Moderate O Low OO Very low OOO Summary of Findings based on impact on patient important outcomes Evidence synthesis (SR or HTA) Recommendation/Decision Grade recommendations For or against (direc1on) Strong or condi1onal/weak (strength) Evidence to decision frameworks q Quality of evidence q Balance benefits/harms q Values and preferences q Feasibility, equity & acceptability q Resource use (if applicable) Guideline Decision Grade overall quality of evidence across outcomes based on lowest quality of critical outcomes Formulate Recommendations ( ) The panel recommends that.should... The panel suggests that.should... The panel suggests to not... The panel recommends to not... Transparency, clear, actionable Research?

52 To conclude.. Building robust DTA data is the start-point Review all the available DTA evidence Explore the link between DTA and Patient important outcomes For a reasonable spectrum of population Balancing benefits and harms of TP, TN, FP, FN and indeterminate results Employing suggesting decision thresholds In a multi-stakeholder team approach

53 Thank you Download this slides at: Hemophilia.mcmaster.ca/resources