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- 1. MRCPsych Teaching 2010 www.slideshare.net/ajmitchell MRCPsych 2010 A. Critical Appraisal of Diagnostic Tests Studies of Accuracy, Validity, Screening & Case finding Alex J Mitchell Consultant in Liaison Psychiatry University of Leicester
- 2. 1. Importance of understanding diagnostic tests 1. Importance of diagnostic tests 2. Concept of diagnostic tests: traits to diseases 3. Statistics of diagnostic tests 4. Clinical Value of diagnostic tests 5. Worked examples 6. Advances techniques
- 3. What Is a Diagnostic Test in Psychiatry? MRCPsych 2010 • CT/MRI • CSF • Blood tests eg TFTs • SCAN/SCID/PSE/MINI • Neuropsychological Testing • MMSE • HADS/BDI/CESD? • Clinical Judgement • Self-report
- 4. Why Is a HADS score not a diagnosis? MRCPsych 2010 1. No core features 2. No symptom ranking 3. No functional assessment 4. Duration unclear 5. What if Missing items? 6. Imprecise
- 5. Defining Diagnostic Testing MRCPsych 2010 INTENTION • Screening – The systematic application of a test or inquiry, to identify individuals at sufficient risk of a specific disorder to warrant further actions among those who have not sought medical help for that disorder • Case-Finding – The selected application of a test or inquiry, to identify individuals with a suspected disorder and exclude those without a disorder, usually in those who have sought medical help for that disorder Adapted from Department of Health. Annual report of the national screening committee. London: DoH, 1997.
- 6. Defining Diagnostic Testing MRCPsych 2010 PRACTICAL • Screening – Rule out those without the disorder with high accuracy (high NPV) • Case-Finding – Rule in those with the disorder with high accuracy (high PPV)
- 7. Defining Diagnostic Testing MRCPsych 2010 APPLICATION • Routine Screening – The systematic application of a test or inquiry, to all individuals who may have (or who have not sought medical help for that disorder) • Targeted (High Risk) – The highly selected application of a test or inquiry, to identify individuals at high risk of a specific disorder by virtue of known risk factors Adapted from Department of Health. Annual report of the national screening committee. London: DoH, 1997.
- 8. Defining Diagnostic Testing MRCPsych 2010 COMPARATOR • Accuracy (aka convergent validity) – The degree of approximation (veracity) to a robust comparator • Validity (aka criterion validity) – The degree of approximation (veracity) to a criterion reference • Precision – The degree of predictability (low SD) in the measure
- 9. Aims of Detection MRCPsych 2010 • Screening: – Short; Easy; some false +ve (low SpS PPV), few false –ve (High Sens, NPV) • Diagnosis (case-finding) – Accurate, Few false +ve or –ve • Rating – Simple, patient rated, correl. With QoL and other outcomes
- 10. UK National Screening Committee Guidelines MRCPsych 2010 • The condition should: • The screening program should: • • Be an important health issue • • Show evidence that benefits of screening • • Have a well-understood history, with a detectable outweighing risks risk factor or disease marker • • Be acceptable to public and professionals • • Have cost-effective primary preventions • • Be cost effective (and have ongoing evaluation) implemented. • • Have quality-assurance strategies in place. • Adapted from: UK National Screening Committee • The screening tool should: Criteria for appraising the viability, effectiveness and • • Be a valid tool with known cut-off appropriateness of a screening programme • • Be acceptable to the public • • Have agreed diagnostic procedures. • http://www.nsc.nhs.uk/pdfs/criteria.pdf • The treatment should: • • Be effective, with evidence of benefits of early intervention • • Have adequate resources • • Have appropriate policies as to who should be treated.
- 11. Development of Diagnostic Tests MRCPsych 2010 Stage Type Purpose Description Pre-clinical Development Development of the proposed tool or Here the aim is to develop a screening method that is likely to help in the detection of the test underlying disorder, either in a specific setting or in all setting. Issues of acceptability of the tool to both patients and staff must be considered in order for implementation to be successful. Phase Diagnostic validity Early diagnostic validity testing in a The aim is to evaluate the early design of the screening method against a known (ideally I_screen selected sample and refinement of tool accurate) standard known as the criterion reference. In early testing the tool may be refined, selecting most useful aspects and deleting redundant aspects in order to make the tool as efficient (brief) as possible whilst retaining its value. Phase Diagnostic validity Diagnostic validity in a representative The aim is to assess the refined tool against a criterion (gold standard) in a real world II_screen sample sample where the comparator subjects may comprise several competing condition which may otherwise cause difficulty regarding differential diagnosis. Phase Implementation Screening RCT; clinicians using vs not This is an important step in which the tool is evaluated clinically in one group with access III_screen using a screening tool to the new method compared to a second group (ideally selected in a randomized fashion) who make assessments without the tool. Phase Implementation Screening implementation studies using In this last step the screening tool /method is introduced clinically but monitored to discover IV_screen real-world outcomes the effect on important patient outcomes such as new identifications, new cases treated and new cases entering remission. Citation: Mitchell AJ. Screening for depression in clinical practice: evidence based approach
- 12. 2. Concepts of Diagnostic Tests: Trait / Syndrome / Disease
- 13. Graphical – Screening principles MRCPsych 2010 # of Individuals Non-Depressed Severity of Depression Depressed # of Individuals
- 14. Graphical – Screening principles MRCPsych 2010 # of Cut-Off Individuals Low High Non-Depressed <<<< high Specificity Severity of Depression High Sensitivity >>>> Depressed # of Individuals
- 15. Graphical – Screening principles MRCPsych 2010 # of Cut-Off Individuals Low High Non-Depressed <<<< low Specificity Severity of Depression High Sensitivity >>>> Depressed # of Individuals
- 16. Graphical – Definition of NPV MRCPsych 2010 Cut-Off Low High True +ve / ALL +ve = PPV Non-Depressed True -ve True +ve Depressed False alarms
- 17. Graphical – Definition of PPV MRCPsych 2010 True –VE / ALL -ve = NPV Cut-Off Low High Non-Depressed True -ve True +ve Depressed Missed cases
- 18. Theory of Diagnostic Tests MRCPsych 2010 Cut-off value Non-Depressed Depressed # of Individuals True -ve True +ve False -ve False +ve Test Result
- 19. Low Prevalence (Se Sp = same) MRCPsych 2010 Cut-off value Non-Depressed Mj Depression # of Individuals False –ve False +ve SMALL LARGE Test Result
- 20. High Prevalence (Se Sp = same) MRCPsych 2010 Cut-off value Non-Depressed Mj+Mn Depression # of Individuals False –ve False +ve LARGE SMALL Test Result
- 21. Can This Help establish a syndrome?
- 22. Example: A Clear Disease [#1] Point of Partial Rarity Number of Individuals No Disorder True ‐ve True ‐ve True +ve True +ve Disorder False +ve False +ve False ‐ve False ‐ve Test Result
- 23. Example: A Probable Syndrome [#2] Number of Individuals No Disorder True ‐ve True ‐ve True +ve True +ve Disorder False +ve False +ve False ‐ve False ‐ve MMSE Cognitive Score
- 24. Example: A Normally Distributed Trait [#3] Number of Individuals No Disorder True ‐ve True ‐ve True +ve True +ve Disorder False +ve False +ve False ‐ve False ‐ve MMSE Cognitive Score
- 25. MRCPsych 2010 Example: Dementia Disease? Syndrome? Trait?
- 26. Hubbert et al (2005) BMC Geriatrics MRCPsych 2010 MMSE scores for dementia (n=72) and non-dementia (n=2735) Huppert et al BMC Geriatrc 2005
- 27. MRCPsych 2010 Example: Depression Disease Syndrome Trait
- 28. 0 500 1000 1500 2000 2500 3000 Ze ro O ne MRCPsych 2010 Tw o Th re e Fo ur Fi ve Si x Se ve n ei gh t N in e Te n El ev en Tw el ve Th irt ee n Fo ur te en Fi fte en Thompson et al (2001) n=18,414 Si xt ee Se n ve nt ee n Ei gh te en
- 29. Mitchell, Coyne et al (2008) MRCPsych 2010 110 100 Scores on the CES-D during Pregnancy, 3 and 12 months Post-partum in 947 Women 90 80 70 60 Early Pregnancy 50 3months Post-Partum 12months Post-Partum 40 30 20 10 0 Healthy Depressive Symptoms Mild Depression Moderate to Severe Depression
- 30. PHQ9 Linear distribution 35 MRCPsych 2010 30 PHQ9 (Major Depression) 25 PHQ9 (Minor Depression) PHQ9 (Non-Depressed) 20 15 10 5 0 ve n en n ro e e o ve n en n ur en en ne x t n gh ee Tw re Te ve n ee Si ee Ze Fo el Fi ev Ni te te O fte Th Ei nt Se Tw irt xt ur gh El Fi ve Th Si Fo Ei Se Baker-Glen, Mitchell et al (2008)
- 31. 3. Statistics of Diagnostic Tests: 2x2s
- 32. Accuracy 2x2 Table Reference Standard Disorder Present Reference Standard No Disorder MRCPsych 2010 Test A/A + B +ve A B PPV Depression Depression Test -ve C D D/C + D NPV PRESENT ABSENT Total A/ A + C D/ B + D Sn Sp Test +ve True +ve False +ve PPV Test -ve False -Ve True -Ve NPV Sensitivity Specificity Prevalence
- 33. Accuracy 2x2 Table MRCPsych 2010 Depression Depression PRESENT ABSENT Test +ve TP FP PPV Test -ve FN TN NPV Sensitivity Specificity Prevalence
- 34. Basic Measures of Accuracy MRCPsych 2010 • Sensitivity (Se) a/(a + c) TP / (TP + FN) • A measure of accuracy defined the proportion of patients with disease in whom the test result is positive: a/(a + c) • Specificity (Sp) d/(b + d) TN / (TN + FP) • A measure of accuracy defined as the proportion of patients without disease in whom the test result is negative • Positive Predictive Value a/(a+b) TP / (TP + FP) • A measure of rule-in accuracy defined as the proportion of true positives in those that screen positive screening result, as follows • Negative Predictive Value c/(c+d) TN / (TN + FN) • A measure of rule-out accuracy defined as the proportion of true negatives in those that screen negative screening result, as follows
- 35. Accuracy in words MRCPsych 2010 • Sensitivity – The chance of testing positive among those with the condition – The chance of rejecting the null hypothesis among those that do not satisfy the null hypothesis • Specificity – The chance of testing negative among those without the condition – The chance of accepting the null hypothesis among those that satisfy the null hypothesis • Positive Predictive Value – The chance of having the condition among those that test positive – The chance of not satisfying the null hypothesis among those that reject the null hypothesis • Negative Predictive Value – The chance of not having the condition among those that test negative – The chance of satisfying the null hypothesis among those that accept the null hypothesis • Type I Error or α (alpha) or p-Value or false positive rate – The chance of testing positive among those without the condition – The chance of rejecting the null hypothesis among those that satisfy the null hypothesis • Type II Error or β (beta) or false negative rate – The chance of testing negative among those with the condition – The chance of accepting the null hypothesis among those that do not satisfy the null hypothesis • False Discovery Rate or q-Value – The chance of not having the condition among those that test positive – The chance of satisfying the null hypothesis among those that reject the null hypothesis • False Omission Rate – The chance of having the condition among those that test negative – The chance of not satisfying the null hypothesis among those that accept the null hypothesis
- 36. Rule-in Accuracy MRCPsych 2010 Depression Depression PRESENT ABSENT Test +ve True +ve False +ve PPV (type I error) (discrimination) Test -ve False –Ve True -Ve NPV (type II error) Sensitivity Specificity Prevalence (occurrence)
- 37. Rule-Out Accuracy MRCPsych 2010 Depression Depression PRESENT ABSENT Test +ve True +ve False +ve PPV Test -ve False –Ve True -Ve NPV (type II error) (discrimination) Sensitivity Specificity Prevalence (occurrence)
- 38. Likelihood Ratios MRCPsych 2010 Likelihood Ratio for Positive Tests The chance of testing positive among those with the condition; divided by the chance of testing positive among those without the condition Sensitivity / (1 - Specificity) [ TP / (TP + FN) ] / [ FP / (FP + TN) ] = PPV / Prevalence Likelihood Ratio for Negative Tests The chance of testing negative among those with the condition; divided by the chance of testing negative among those without the condition Specificity / (1 – Sensitivity) [ FN / (FN + TP) ] / [ TN / (TN + FP) ] = NPV / Prevalence
- 39. Summary Measures MRCPsych 2010 • Youden's J – Sensitivity + Specificity – 1 • Predictive Summary Index – PPV + NPV – 1 • Overall accuracy (fraction correct) – TP+TN / TP+FP+TN+FN
- 40. Reciprocal Measures MRCPsych 2010 • Number Needed to Diagnose (NND) – 1 / (Youden's J) • Number Needed to Predict (NNP) – 1 / (PSI) • Number Needed to Screen (NNS) – 1/(FC-FiC)
- 41. Receiver Operating Characteristic Murphy JM, Berwick DM, Weinstein MC, Borus JF, Budman SH, Klerman GL 1987 : Performance of screening and diagnostic tests: Application of Receiver Operating Characteristic ROC analysis. Arch Gen Psychiatry 44:550-555
- 42. Accuracy 2x2 Table MRCPsych 2010 Depression Depression PRESENT ABSENT Test +ve True +ve False +ve PPV Test -ve False -Ve True -Ve NPV Sensitivity Specificity Prevalence
- 43. Test vs Major Depression MRCPsych 2010 Depression Depression PRESENT ABSENT Test +ve 500 1500 2000 PPV 25% Test -ve 500 4500 5000 NPV 90% 1000 6000 7000 Sensitivity Specificity Prevalence 14% 50% 75%
- 44. Test vs Major + Min Depression MRCPsych 2010 Depression Depression PRESENT ABSENT Test +ve 500 1500 2000 PPV 25% Test -ve 500 500 1000 NPV 50% 1000 2000 3000 Sensitivity Specificity Prevalence 33% 50% 33%
- 45. 4. Clinical Value of Diagnostic Tests
- 46. Added Value MRCPsych 2010 • Definition 1: – The additional ability of a test to rule-in or rule-out compared with the baseline rate – PPV minus Prevalence – NPV minus prevalence • Definition 2: – The additional of a test to rule-in or rule-out compared with the unassisted rate – PPV test minus PPV no test (assuming equal prevalence) – LR+ test minus LR+ no test – AUC test minus AUC no test
- 47. 0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00 Loss of energy Diminished drive Sleep disturbance MRCPsych 2010 Concentration/indecision Depressed mood Anxiety Diminished concentration Insomnia Diminished interest/pleasure Psychic anxiety Helplessness Worthlessness Hopelessness Somatic anxiety Thoughts of death Anger Excessive guilt Psychomotor change Indecisiveness Decreased appetite Psychomotor agitation Psychomotor retardation Decreased weight Lack of reactive mood Increased appetite All Case Proportion Hypersomnia Depressed Proportion Non-Depressed Proportion Increased weight Mitchell, Zimmerman et al MIDAS Database. Psychol Med 2007 Submitted
- 48. -0.10 0.00 0.10 0.20 0.30 0.40 0.50 A nge r A nxie ty Decr ea s e d app eti te MRCPsych 2010 Decr eas e d weig ht Depr es sed m ood Dimin is hed c onc entr a t io n Dimin is hed dr ive Dimin is hed int er est /p leasu re Exc e ss ive guilt Help less n ess Hope le s snes s Hy pe rsom ni a Inc re a sed a ppet ite Inc re a sed w eight Indec isiv enes s Ins om nia L ac k of re act iv e mo od L os s of en erg y Ps ych i c a nx iety Ps ych o mot o r agi ta tion Ps ych o mot o r c han ge Ps ych o mot o r ret ar da tion Sl eep dis tu rban ce Soma ti c a nx iet y Rule-In Added Value (PPV-Prev) Thou g hts Rule-Out Added Value (NPV-Prev) of de ath Wor t hles s ness
- 49. Accuracy of Tests: Visual Post-test Probabilities MRCPsych 2010 Very unlikely unlikely likely Very likely Overall 10% - (22) -50% = 54% CIDI (computer) Any Depression PHQ-2 3% - (16) - 32% = 29% Henckel et al (2004) Eur Arch Psychiatry Clin Neurosci CIDI (computer) Any Depression WHO5 (1+3) 3% - (16) - 32% = 29% Henckel et al (2004) Eur Arch Psychiatry Clin Neurosci CIDI (computer) Mj Depression 1 Question 3% - (37) - 63% = 60% Arroll B et al (2003) BMJ CIDI (computer) Mj Depression 2 Questions 25% 75% 0% 32% - (37) - 96% = 64% 100%
- 50. 1.00 MRCPsych 2010Post-test Probability 0.90 0.80 0.70 0.60 0.50 0.40 Clinician Positive (Fallowfield et al, 2001) 0.30 Clinician Negative (Fallowfield et al, 2001) Baseline Probability 0.20 HADS-D Positive (Mata-analysis) HADS-D Negative (Meta-analysis) 0.10 Pre-test Probability 0.00 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
- 51. 1.00 Post-test Probability Depression Present (Routine) 0.90 Depression Absent (Routine) MRCPsych 2010 Depression Scales +ve (Median) 0.80 Depression Scales -ve (Median) Prior Probability 0.70 0.60 0.50 PPV=0.41 0.40 0.30 0.20 0.10 NPV=0. 97 Pre-test Probability 0.00 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 Prevalence of 0.15
- 52. 5. Worked Examples of diagnostic tests
- 53. PostStroke Mj Depression vs NonMj MRCPsych 2010 • Clinicians diagnosis using DSMIV vs SCAN/PSE – 50 people with major depression – 150 healthy people – 50 with subsyndromal depression
- 54. Clinicians using DSMIV MRCPsych 2010 • IF: Clinicians diagnosed 50 cases with Mj depression • IF: Their specificity was 95% • Q. What was the sensitivity? • Q. What was the prevalence? • Q. What was the PPV? • Q. What was the % correctly identified per every 100 screened?
- 55. Test vs Major Depression MRCPsych 2010 Depression Depression On SCAN ABSENT Test +ve ?? 50 (Clinician) PPV ??% Test -ve ?? NPV ??% 50 200 Sensitivity Specificity Prevalence ??% 50% 95%
- 56. Test vs Major Depression MRCPsych 2010 Depression Depression On SCAN ABSENT Test +ve 40 10 50 (Clinician) PPV 80% Test -ve 10 190 200 NPV 95% 50 200 Sensitivity Specificity Prevalence 20% 80% 95%
- 57. 6. Advanced Techniques sROC Real World Numbers NND; NNS Bivariate meta-analysis Economics
- 58. 1.00 MRCPsych 2010 ROC Plot 0.90 Low Mood Sensitivity 0.80 DSMIV 0.70 Low mood & loss interest 0.60 0.50 0.40 0.30 0.20 0.10 0.00 0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00 1 - Specifity
- 59. MRCPsych 2010
- 60. Bivariate Diagnostic meta-analysis MRCPsych 2010
- 61. Further Reading MRCPsych 2010 • David A Grimes, Kenneth F Schulz Uses and abuses of screening tests Lancet 2002; 359: 881–84 • Jonathan J Deeks, Douglas G Altman Diagnostic tests 4: likelihood ratios BMJ VOLUME 329 17 JULY 2004 • Patrick M Bossuyt, Les Irwig, Jonathan Craig and Paul Glasziou Comparative accuracy: assessing new tests against existing diagnostic pathways. BMJ • 2006;332;1089-1092 • Reitsma JB et al Bivariate analysis of sensitivity and specificity produces informative summary measures in diagnostic reviews. Journal of Clinical Epidemiology 58 (2005) 982–990
- 62. MRCPsych Teaching 2010 MRCPsych 2010 B. Critical Appraisal of Prognostic Tests Risk, predictors, measuring outcomes Alex J Mitchell Consultant in Liaison Psychiatry University of Leicester
- 63. Measuring Risk MRCPsych 2010 Risk – the probability of some untoward event •e.g., disease, death Risk Factor – characteristics or behaviours associated with an increased risk of becoming diseased
- 64. Healthy Healthy Healthy With SMC MCI With SMC FTD Dementia VaD AD LBD Mixed
- 65. Modelling Progression on MCI-Dementia MRCPsych 2010 Disease Severity Healthy MMSE 30 MCI 23v24 Mild Dementia 20v21 Moderate Dementia 11v12 Severe Dementia 0 T0 T4 T+8 T+12 Time in Years
- 66. Modelling Progression on MCI-Dementia MRCPsych 2010 Disease Severity Healthy MMSE 30 MCI 23v24 Mild Dementia 20v21 Moderate Dementia 11v12 Severe Dementia 0 T0 T4 T+8 T+12 Time in Years
- 67. Modelling Progression on MCI-Dementia MRCPsych 2010 Disease Severity Healthy MMSE 30 MCI MCI-Progressive Moderate Risk 23v24 Mild Dementia MCI-Progressive 20v21 High Risk Moderate Dementia 11v12 Severe Dementia 0 T0 T4 T+8 T+12 Time in Years
- 68. Accuracy 2x2 Table MRCPsych 2010 OUTCOME OUTCOME PRESENT/ ABSENT / POOR GOOD RISK +ve True +ve False +ve PPV of predictor RISK -ve False -Ve True -Ve NPV of predictor Sensitivity Specificity Prevalence Of of predictor predictor
- 69. Test for AD vs HC…fill in missing cells MRCPsych 2010 AD MCI Test +ve 600 100 700 PPV 85.0% Test -ve NPV 81% 800 1000 1800 (44%) Mitchell (2005) Sensitivity Specificity Meta-analysis 75% 90% N=14x
- 70. Test for AD vs HC…..good test? MRCPsych 2010 AD MCI Test +ve 600 100 700 PPV 85.0% Test -ve 200 900 1100 NPV 81% 800 1000 1800 (44%) Mitchell (2005) Sensitivity Specificity Meta-analysis 75% 90% N=14x
- 71. 1.00 MRCPsych 2010 0.90 Post-test Probability 0.80 0.70 0.60 0.50 Test+ 0.40 Test- 0.30 Baseline Probability 0.20 0.10 Pre-test Probability 0.00 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
- 72. 1.00 MRCPsych 2010 0.90 Post-test Probability 0.80 0.70 0.60 0.50 Test+ Test- 0.40 Baseline Probability 0.30 Clinician+ 0.20 Clinician- 0.10 Pre-test Probability 0.00 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
- 73. AD vs HC – P-Tau181 MRCPsych 2010 AD MCI Test +ve 595 113 708 PPV 84.0% Test -ve 257 576 833 NPV 69.1% 852 689 1541 Mitchell (2005) Sensitivity Specificity Meta-analysis 69.8% 83.6% N=14x
- 74. Classifying Predictors MRCPsych 2010 Demographic Disease Related • Age • MCI Type • Gender • MCI Subtype • Education • Structural Imaging Service Related • Functional Imaging • CSF Studies • Recruitment Setting • Genetic testing (ApoE4) • Education • Cognitive Testing • Length of follow-up • Non-memory impairment • Delay in diagnosis • Depression/anxiety • Treatment • Subjective Performance • Size of study • Functional status • Vascular status
- 75. Mayo Data Survival (Kaplan-Mayer) MRCPsych 2010 100 Normals Normals All amnestic MCI All amnestic MCI 80 A-MCI single domain A-MCI single domain A-MCI multidomain A-MCI multidomain 60 Alive (%) 40 20 P<0.023 P<0.023 0 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 Years after enrollment CP1183493-11
- 76. Measuring Risk MRCPsych 2010 • Absolute Risk Reduction (ARR) – is the absolute difference in event rates between the experimental and control patients. ARR = CER - EER • Number Needed to Treat (NNT) – is the number of patients a clinician needs to treat in order to prevent one additional adverse outcome
- 77. Measuring Risk - Examples MRCPsych 2010 CER EER RRR ARR NNT 0 .6 0 .4 33% 20% 5 0 .0 6 0 .0 4 33% 2% 50 0 .0 0 6 0 .0 0 4 33% .2 % 500 RRR remains the same despite differences in absolute rate of events. ARRs reflect underlying susceptibility of patients NNTs provide a measure of the clinical effort that must be expended
- 78. Checklist criteria MRCPsych 2010 • Are the study population similar to our patients? • Is the study design appropriate for the research question? • Were the study subjects representative of patients with the disease in question? • Were the patients at a similar point in the course of their disease? • Were the outcomes objectively-defined, and were the people recording the outcomes blinded to the prognostic factors? • Were patients followed long enough for outcomes to occur? • Was the dropout rate excessive? • Did the authors adjust for differences between groups?

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