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## Clinical Epidemiology

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**Clinical Epidemiology**Using Evidence to Guide Practice A bit of thinking and a few simple sums**What you need to know for the MRCGP**“Sums” • ARR, RRR, NNT (calculate) plus OR • Impact of baseline risks • P values, Confidence Intervals (principles, not how to calculate) • Power (principles) • Diagnosis and screening • Sensitivity, specificity, PPV, NPV (LRs unlikely?) Concepts • Types of studies, including SR & MA, qualitative research (principles), health economics (principles) • Where to find evidence (in the real world) • How to use EBM in the consultation**Who likes shopping?(Oh no, I really hate that)**Apples – were £30 a bag, now only £20 a bag. • Saving is £10 per bag (Original rate – new rate). • Saving is one third or 33%. (original rate – new rate / original rate; i.e. 3-2 = 1, 1/3 = one third, 1/3 x 100 = 33% • Apples – 3p a bag, now 2p a bag • Saving is 1p a bag • Saving is STILL one third Would you go out and buy apples if the saving was ONLY described as “ONE THIRD OFF”?**Describing differences between treatments**• In a RCT, 50% of people died using medicine A. • Only 45% of people died when they were given medicine B. • How much better is B than A? • Does it matter how we describe those differences? • What is the best way, or the “fairest way”, of describing differences?**In a RCT, 50% of people died using medicine A. Only 45% of**people died when they were given medicine B. • The difference is 5%. (Control rate – experimental rate = 50% - 45% = 5%.) Absolute risk reduction (ARR) or risk difference • The difference is 10%. Control rate – experimental rate / control rate; 50% - 45% = 5% / 50% = 1/10 = 10%. Relative risk reduction (RRR) or risk ratio Which of these is “best” or “fairer”?**Same medicines, different people**In a RCT, 5% of people died using medicine A. Only 4.5% of people died when they were given medicine B. • The difference is 0.5%. (Control rate – experimental rate = 5% - 4.5% = 0.5%.) ARR = 0.5%. • The difference is 10%. Control rate – experimental rate / control rate; 5% - 4.5% = 0.5% / 5% = 1/10 = 10%. RRR = 10%.**So let’s get this straight**• The RRR stays constant in different populations. • The ARR alters in different populations – it will be much more impressive if the population has a lot of events – i.e. “has a high baseline risk”. • But if there are not many events then a 10%, 20% or even a 30% reduction in a rare event doesn’t amount to much benefit. And EVERYBODY has to take the intervention (and so is at risk of side effects).**Numbers needed to treat (NNT)**Medicine A cures 50% of people Medicine B cures 60% of people ARR = 10% RRR = 20% Another way of looking at the absolute rate is to divide it into 100: • In this case 100/10 = 10. • i.e. treat ten people with B rather than A and 1 will benefit.**Same medicines, different people again**In RCT 1: • 50% of people died using medicine A • Only 45% of people died using medicine B. • ARR 5%, RRR 10%,NNT 20. • In RCT 2: • 5% of people died using medicine A. • Only 4.5% of people died using medicine B. • ARR = 0.5%. RRR = 10%. NNT = 200. In the higher risk population, we would only need to treat20 people with B rather than A to save one. But in the lower risk population we would need to treat200 people with B rather than A to save one.**Effect of baseline risk on ARR**Event = a coronary death or a non-fatal MI 4S 2% ARR 1% CARE WOSCOPS LIPID ACTC 0% 0% 6% 1% 2% 3% 4% 5% Baseline annual risk of an event**Mini-test (1)**Calculate the ARRs, RRRs and NNTs for these trials: • Medicine A 15% have an MI, Medicine B 12% have an MI. • Medicine A 7% have an epileptic fit, Medicine B 5% have an epileptic fit. • Medicine A 12% develop diabetic retinopathy, Medicine B 6% develop diabetic retinopathy. • Medicine A 27% are readmitted with heart failure, Medicine B, 24% are readmitted with heart failure.**Mini-test (1) answers**Calculate the ARRs, RRRs and NNTs for these trials: ARR RRR NNT • 3% 20% 33 • 2% 29% 50 • 6% 50% 17 • 3% 11% 33**Clopidogrel in ACS**• It’s really beneficial; I’d want all of my patients to be taking it • Most people do fine just on aspirin. Adding clopidogrel prevents only a few people having an event and there’s the increased bleeding risk • The specialist starts it and I don’t question that**20% relative risk reduction**2.1% absolute risk reduction NNT 48 38% relative risk increase 1% absolute risk increase NNT 100 N Engl J Med 2001; 345: 494-502.**Translation: Clopidogrel significantly reduces the**absolute risk of: • CV Death, MI, Stroke taken together by 2.1% (p < 0.001) NNT 48 • CV Death, MI, Stroke, and Refractory Ischaemia taken together by 2.3% (p < 0.001) NNT 43 • Most benefit is achieved by 30 days with MI • There is no effect on all cause mortality • There is a large (relative 38%) significant excess of major bleeds**This is appallingNuovo J, et al. JAMA 2002; 287: 2813 –4.**• Ann Intern Med, BMJ, JAMA, Lancet, NEJM • 1989, 1992, 1995, 1998. • Treatment RCTs • 359 eligible articles. • NNT reported in 8 (6 of these in 1998) • ARR reported in 18 (10 of these in 1998). Put another way, 93% of all RCTs only report relative risk.**Odds ratios or relative risks?Macfarlane J et al. BMJ 2002;**13: 105-9**Relative risk: (49/104) / (63/101) = 0.76.**i.e the relative risk of patients taking an antibiotic if they were given a leaflet is reduced by 24%. (Also called risk ratio)**Odds ratio: (49/55) / (63/38) = 0.54.**There was a 46% reduction in the ratio of those taking antibiotics who had a leaflet compared with the ratio of those taking antibiotics who did not have a leaflet.**Absolute risk reduction: (63/101) – (49/104) = 0.15.**Also known as the risk difference. i.e. the difference in the risk of taking antibiotics depending on whether a leaflet was used or not.**NNT: 1 / 0.15 = 7. i.e. 7 people need to be given a leaflet**In order for 1 additional person not to take antibiotics**What you need to know for the MRCGP**• ARR, RRR, NNT (calculate) – plus OR • Impact of baseline risks • P values, Confidence Intervals (principles, not how to calculate) • Power (principles) • Diagnosis and screening • Sensitivity, specificity, PPV, NPV (LRs unlikely) • Types of studies, including SR & MA, qualitative research (principles), health economics (principles) • Where to find evidence (in the real world) • How to use EBM in the consultation**matters**Size**How does the size of the study affect things?Counsell CE, et**al. BMJ 1994 309: 1677-1681. [Bandolier Nov 2002] • Investigators used a dice to simulate outcomes in a trial • ‘Treatment’ arm vs. control arm • Roll of a dice = outcome in the trial: • 1-5 survival • 6 = death • Did for ‘treatment’ group then repeated for control group • Number of times the dice was rolled varied from 5 to 100.**But it’s the size that matters**More consistency in results Wide variation in results • Results according to number of times the dice was rolled: • Variation in ‘outcome’ was largest in the ‘smallest’ studies • i.e the chance of a spurious result decreased with increasing numbers included in the trial**How good is the evidence for the management of schizophrenia**Thornley B, et al. BMJ 1998; 317: 1181-84 Size of trials (n=1941; 59 studies did not report study size)**Sub-group analyses – caveat emptor**ISIS 2 trial: • 17,187 patients, 417 hospitals up to 24 hours after MI. • Randomised to either streptokinase, aspirin or placebo in 2x2 factorial design • Streptokinase alone and aspirin alone each produced a highly significant reduction in 5-week vascular mortality: ARR 2,8%, together ARR vs double placebo 5.2%. • To try and allay concerns re benefit:safety ratio in subgroups, the Lancet pushed for subgroup analyses. • The authors agreed – but with the proviso that they should analyse by astrological star signs and that this should appear first in the table of subgroup results. • The result? Gemini and Libra: aspirin of no benefit. All other star signs: aspirin strongly beneficial**What you need to know for the MRCGP**• ARR, RRR, NNT (calculate) – plus OR • Impact of baseline risks • P values, Confidence Intervals (principles, not how to calculate) • Power (principles) • Diagnosis and screening • Sensitivity, specificity, PPV, NPV (LRs unlikely) • Types of studies, including SR & MA, and qualitative research (principles) • Where to find evidence (in the real world) • How to use EBM in the consultation**P< 0.05**The Sacred P-Value The Shrine of Statistics**Did he just say P = 0.05 ????**P = 0.027 means…… this result occurs BY CHANCE 1 time in 36; If P = 0.0001, 1 time in 10,000 by chance**Confidence intervals are the range of values between which**we could be 95% certain that this result would lie if this intervention was applied to the general population**Confidence Intervals**Estrogen Replacement Therapy in Women with a History of Proliferative Breast Disease**Confidence intervals are the range of values between which**we could be 95% certain that this result would lie if this intervention was applied to the general population Since the 95% CI crosses 1.0, the difference is not significant 95% C.I. 1.2 0.68 0.91 Risk could be this high Risk could be this low 1.0**Silverstein FE, et al. JAMA 2000; 284: 1247-1255**6 month data: Incidence rate per year Celecoxib NSAIDs NNT All patients: upper GI ulcer complications alone 0.76% 1.45% (P=0.09) - combined with symptomatic ulcers 2.08% 3.54% (P=0.02) 68 For patients not taking aspirin: upper GI ulcer complications alone 0.44% 1.27% (P = 0.04) 121 combined with symptomatic ulcers 1.40% 2.91% (P= 0.02) 66 For patients taking aspirin: upper GI ulcer complications alone 2.01% 2.12% (P = 0.92) - combined with symptomatic ulcers 4.70% 6.00% (P = 0.49). -**Kaplan-Meier estimates for ulcer complications according to**traditional definitionJüni P, et al. BMJ 2002; 324: 1287-1288**What you need to know for the MRCGP**• ARR, RRR, NNT (calculate) – plus OR • Impact of baseline risks • P values, Confidence Intervals (principles, not how to calculate) • Power (principles) • Diagnosis and screening • Sensitivity, specificity, PPV, NPV (LRs unlikely) • Types of studies, including SR & MA, qualitative research (principles), health economics (principles) • Where to find evidence (in the real world) • How to use EBM in the consultation**B**C No Disease Disease A Percent of population 0 10 20 30 VALUE Arbitrary Units Set cut off at A A lot of people who do not have the disease are labeled as having it (false positives) A lot of people who do have the disease are labeled as not having it (false negatives) Set cut off at B**How many people in the study?**Disease Present Absent Positive Test Negative 100**How many had the disease?**Disease Present Absent Positive Test Negative 50 50 100**How many with the disease had a positive test?How many**without the disease had a negative test? Disease Present Absent Positive 50 45 5 Test 50 Negative 5 45 50 50 100**What was the prevalence of disease in those tested?**Disease Present Absent Positive 45 5 50 Test 50 Negative 5 45 50 50 100 Prevalence = 50/100 = 50%**So …………Sensitivity and specificity**Disease Present Absent Positive 50 45 5 Test 50 Negative 5 45 50 50 100 5/50 false negatives; i.e. sensitivity = 45/50 =90% 5/50 false positives; i.e. specificity = 45/50 = 90%**Positive Predictive Value and Negative Predictive Value**Disease Present Absent PPV 45/50 = 90% Positive 50 45 5 Test 50 Negative 5 45 NPV 45/50 = 90% 50 50 100**Watch what happens when the prevalence drops to 10%NB.**PLEASE remember this bit!!!!!!! Disease PPV 9/18 = 50% Present Absent Positive 18 9 9 Test 82 Negative 1 81 NPV 81/82 = 99% 10 90 100 Prevalence = 10/100 = 10% 1/10 false negatives; i.e. sensitivity = 9/10 =90% 9/90 false positives; i.e. specificity = 81/90 = 90%**H Pylori infection in a population with a 25%**prevalenceMeReC Bulletin 2001; 12 (1): 1-4 Sensitivity (%) Specificity (%) Positive predictive value (%) Negative predictive value (%) False positive results (%) False Negative results (%) Breath test (13C) 96.5 96 89 99 11 1 Breath test (14C) 97.5 95.5 88 99 12 1 Laboratory serological tests 91 90 75 97 25 3 Near-patient serological tests 86 75.5 54 94 46 6**So what does all this mean?**• In primary care many people have a low chance of having the disease they are being tested for. • If they get a positive test then they may have the disease – or it could be a false positive. They may need more tests to sort out whether they truly, truly have the disease. • (But what will the patient think when you tell them their initial test indicates they may have something and they need further tests?) • If they get a negative test, and they are unlikely to have the disease, then it’s really very unlikely that they have it when they have tested negative. • And MOST IMPORTANTLY, try only to test people for anything if they are in a high risk group for having the disease. Testing lots of people will do more harm than good.**What you need to know for the MRCGP**“Sums” • ARR, RRR, NNT (calculate) – plus OR • Impact of baseline risks • P values, Confidence Intervals (principles, not how to calculate) • Power (principles) • Diagnosis and screening • Sensitivity, specificity, PPV, NPV (LRs unlikely) Concepts • Types of studies, including SR & MA, qualitative research (principles), health economics (principles) • Where to find evidence (in the real world) • How to use EBM in the consultation**My brain hurts**Mr T F Gumby