Turning a clinical question into a testable hypothesis
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Turning a clinical question Turning a clinical question into a testable hypothesisinto a testable hypothesis
Turning a clinical question Turning a clinical question into a testable hypothesisinto a testable hypothesis
Lauren A. Trepanier, DVM, PhDLauren A. Trepanier, DVM, PhD
Diplomate ACVIM, Diplomate ACVCPDiplomate ACVIM, Diplomate ACVCP
Department of Medical SciencesDepartment of Medical Sciences
School of Veterinary MedicineSchool of Veterinary Medicine
University of Wisconsin-MadisonUniversity of Wisconsin-Madison
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Clinical questionsClinical questionsClinical questionsClinical questions
• Trust your clinical experienceTrust your clinical experience• Common diseasesCommon diseases• Clinical controversiesClinical controversies• Standards of practice in Standards of practice in
human patientshuman patients
Clinical questionsClinical questionsClinical questionsClinical questions
• New diagnostic testsNew diagnostic tests• Better treatment optionsBetter treatment options• Characterization of outcomesCharacterization of outcomes• Prognostic indicatorsPrognostic indicators• Underlying etiologyUnderlying etiology
Getting ideasGetting ideasGetting ideasGetting ideas
• Journal club papersJournal club papers• Logical follow-upsLogical follow-ups
• Specialty proceedingsSpecialty proceedings• Knowledge gapsKnowledge gaps
•Discussions with senior Discussions with senior facultyfaculty
Define the state of knowledge Define the state of knowledge Define the state of knowledge Define the state of knowledge
• Literature searchLiterature search• Multiple search termsMultiple search terms• Reference lists from papersReference lists from papers• Read full papers!!Read full papers!!•Beware abstracts that never Beware abstracts that never made it to peer reviewed pubsmade it to peer reviewed pubs
Define the knowledge gapDefine the knowledge gapDefine the knowledge gapDefine the knowledge gap
• Major conclusions from each paperMajor conclusions from each paper• Organize as a logical storyOrganize as a logical story•Why it is importantWhy it is important•What is known in humansWhat is known in humans•What is known in veterinary What is known in veterinary
species of interestspecies of interest
Refining the clinical questionRefining the clinical questionRefining the clinical questionRefining the clinical question
• What remains to be answered?What remains to be answered?• Does your question need Does your question need
revising?revising?• What do you think you will What do you think you will
find (your hypothesis)?find (your hypothesis)?
Framing your research approachFraming your research approachFraming your research approachFraming your research approach
• Research objectives, or aims, to Research objectives, or aims, to specifically test your hypothesisspecifically test your hypothesis• To compareTo compare• To determineTo determine• To evaluateTo evaluate• To characterizeTo characterize
PICOT approachPICOT approachPICOT approachPICOT approach
• PopulationPopulation• InterventionIntervention• ComparatorsComparators• OutcomesOutcomes• Time frameTime frame
PopulationPopulationPopulationPopulation
• Inclusion criteriaInclusion criteria• Gold standard for Gold standard for
diagnosisdiagnosis• Validated surrogate Validated surrogate
markermarker
smallanimal.vethospital.ufl.edusmallanimal.vethospital.ufl.edu
PopulationPopulationPopulationPopulation
• Inclusion criteriaInclusion criteria• Specific breed(s)Specific breed(s)• Stage of diseaseStage of disease• Severity of illnessSeverity of illness
•Heterogeneity vs. Heterogeneity vs. homogeneityhomogeneity
PopulationPopulationPopulationPopulation
• Exclusion criteriaExclusion criteria• Prior treatments allowed?Prior treatments allowed?• WashoutWashout• Patient size vs. blood drawnPatient size vs. blood drawn• Exclude fractious animals?Exclude fractious animals?• Owner consentOwner consent
InterventionInterventionInterventionIntervention
• Drug treatmentDrug treatment• Surgical procedureSurgical procedure• Diagnostic assayDiagnostic assay
• What other care is allowed?What other care is allowed?•Avoid “clinician discretion” Avoid “clinician discretion” without guidelineswithout guidelines
InterventionInterventionInterventionIntervention
• Blinded vs. double blindedBlinded vs. double blinded• Applies to all evaluatorsApplies to all evaluators• OwnersOwners• Managing cliniciansManaging clinicians• Techs administering Techs administering
questionnairesquestionnaires• RadiologistsRadiologists• PathologistsPathologists
ComparatorsComparatorsComparatorsComparators
• Clinically relevantClinically relevant• Normal or suspected Normal or suspected
of disease?of disease?• Placebo or standard Placebo or standard
of care?of care?• ConcurrentConcurrent• RandomizedRandomized
RandomizationRandomizationRandomizationRandomization
• Random numbersRandom numbers• Evaluators should be Evaluators should be
blinded to schemeblinded to scheme
Random Numbers00531 41784 44584 62742 81710 71692 28303 58470 94527 33239 70219 59279 38984 99868 17217 18285 15081 24694 95854 82373 96259 54602 79573 78101 09076 16149 21490 05468 53534 82778 68487 37916 03072 07604 47125 02004 10808 37512 57402 97732 23626 99059 72760 25098 68083 65688 19758 84105 17622 90514 98395 48193 98800 20421 08672 43920 38175 81969 24030 71287 56074 48597 71028 03736 32171 73424 49666 67824 13349 03331 59942 63551 26167 64879 75301 90918 70624 31507 48857 49925 46720 56333 00936 14013 27898 86241 11213 09740 40716 47788 53129 37107 85173 14417 00127 69556 34712 39243
OutcomesOutcomesOutcomesOutcomes
• Define a primary outcomeDefine a primary outcome• ObjectiveObjective• Easily measuredEasily measured• Clinically availableClinically available• Validated for your speciesValidated for your species• Relevant to clinical responseRelevant to clinical response
Dr. Noel Moens, GuelphDr. Noel Moens, Guelph
OutcomesOutcomesOutcomesOutcomes
• Subjective primary outcomesSubjective primary outcomes• Validated scoring systemValidated scoring system• Complement with objective Complement with objective
outcomes whenever possibleoutcomes whenever possible• Blinded evaluators!!Blinded evaluators!!
Dr. Duncan Lascelles, NCStateDr. Duncan Lascelles, NCState
OutcomesOutcomesOutcomesOutcomes
• Secondary outcomesSecondary outcomes• Less important?Less important?• May be harder to proveMay be harder to prove•Can generate further Can generate further hypotheseshypotheses• Add depthAdd depth
Sample size and powerSample size and powerSample size and powerSample size and power
• Both prospective and Both prospective and retrospective designsretrospective designs
• Need enough cases to Need enough cases to overcome variability overcome variability withinwithin groups to show groups to show a difference a difference betweenbetween groupsgroups
Healthy Dog GSH Sick Dog GSH0
1
2
3
4PP = 0.0004 = 0.0004
Viviano et al. Viviano et al. J Vet Intern MedJ Vet Intern Med. 2009 . 2009
Sample size calculationSample size calculationSample size calculationSample size calculation
• Type I error: finding a Type I error: finding a difference when it is difference when it is actually due to chanceactually due to chance
• Type II error: missing a Type II error: missing a difference that is actually difference that is actually presentpresent
• With too few cases, you With too few cases, you can have can have eithereither type type
PowerPowerPowerPower
• Type I error: P = 0.05Type I error: P = 0.05• Type II error: often set at Type II error: often set at
10-20% 10-20%
• Power = 100 -Type II errorPower = 100 -Type II error• Power = ability to detect a Power = ability to detect a
true difference true difference • Power often set at 80-90%Power often set at 80-90%
Sample size (or power) calculationSample size (or power) calculationSample size (or power) calculationSample size (or power) calculation
• Two approaches:Two approaches:• Start with known Start with known
sample size and sample size and calculate the power calculate the power to find a differenceto find a difference
• Set a minimum Set a minimum power and calculate power and calculate needed sample sizeneeded sample size
Healthy Dog GSH Sick Dog GSH0
1
2
3
4
Sample size (or power) calculationSample size (or power) calculationSample size (or power) calculationSample size (or power) calculation
• Choose your stats test Choose your stats test based on type of databased on type of data
• Define the variability Define the variability in your control in your control population (SD)population (SD)
• Define the difference Define the difference you need to detectyou need to detect
http://www.stat.uiowa.edu/~rlenth/Power/
Sample sizeSample sizeSample sizeSample size
• Consider drop-outConsider drop-out
Time frame Time frame Time frame Time frame
• Recruitment periodRecruitment period
• Timing of interventionTiming of intervention• Duration of interventionDuration of intervention• Time points for evaluationTime points for evaluation
Time frame Time frame Time frame Time frame
• Consider seasonal Consider seasonal variablesvariables• Follow-upFollow-up• Complicated?Complicated?• Prolonged?Prolonged?
Finalized PICOT research planFinalized PICOT research planFinalized PICOT research planFinalized PICOT research plan
• Still addresses the hypothesisStill addresses the hypothesis• Still relevantStill relevant• Feasible!Feasible!• Clinical expertiseClinical expertise• CaseloadCaseload• Support staffSupport staff• FundsFunds• Career time frameCareer time frame
Finalized PICOT research planFinalized PICOT research planFinalized PICOT research planFinalized PICOT research plan
• Question is of interest to pet Question is of interest to pet ownersowners• Intervention is low riskIntervention is low risk• Follow-up is convenientFollow-up is convenient• Incentives are consideredIncentives are considered
Common roadblocksCommon roadblocksCommon roadblocksCommon roadblocks
• Disease is uncommonDisease is uncommon• Studied outcome is rareStudied outcome is rare• Data collection too labor Data collection too labor
intensiveintensive
Common roadblocksCommon roadblocksCommon roadblocksCommon roadblocks
• Samples banked without Samples banked without validated assays (!)validated assays (!)• Case identification out Case identification out
of your controlof your control• Collaborators Collaborators
unmotivatedunmotivated
Key pointsKey pointsKey pointsKey points
• Study what you knowStudy what you know• Choose straight-forward Choose straight-forward
aims using available aims using available assays/proceduresassays/procedures• Define the approach Define the approach
using PICOTusing PICOT
Key pointsKey pointsKey pointsKey points
• Make sure you would Make sure you would volunteer your own pet volunteer your own pet to participateto participate• Results should be Results should be
publishable no matter publishable no matter what the outcomewhat the outcome
Questions or comments?Questions or comments?