1. Treatment Considerations And Bias Dosages, potency, inclusion/exclusion, study setting

2. What is Bias?  Systematic (or introduced) error that leads to data distortion (skewing) and hence, to an incoherent conclusion Subject selection bias  Study design  Random sampling  Randomization – are groups equal  Inclusion/exclusion criteria

3. Data Collection Bias  Method selected for data collection  Measuring method Validity and reproducibility of instrument used to measure Blinding

4. Investigator Bias  Journal study is published in  Drug company funding?– (don’t automatically reject the study!)  Value statements in results/discussion that are unsupported by literature (citations, statistics from current study)  Statistical vs. clinical significance  Use of the word “significance”

5. Bias with “Significance”  Obstructive symptom score in Men with BPH treated with Finasteride or Placebo  GroupBaseline score12 mo. Score  Placebo 6.7 +3.55.9 + 3.8  1 mg Finas. 7.4 + 3.86.0 + 3.8 *  5 mg Finas. 7.0 + 3.65.1+ 3.6 *  * Statistically significantly different from placebo.

6. Confounding variables  Something the investigators did NOT do or failed to consider, which may have influenced the outcome/results. Pharmacokinetics Side effects Demographics of study population Pharmacogenetics – race, gender, age Compliance Dosages Study setting

7. Dosages  Must be administered in a dose likely to produce benefit  There is no single or standard relationship between the intensity of response and dose (dose response curve) which can be uniformly applied to all drugs.  Variation small increase in dose can cause large response large increase in dose can cause small response

8. Potency  Because 1 drug is more potent than another on a mg to mg basis, this does not imply clinical superiority.  Potency is not important when comparing efficacy if they are equivalent doses  Doses for active controls should also be comparable to those of the study drug  Use of fixed doses could be inappropriate

9. Fixed Doses  Problems with a fixed dose study might not be applicable to “real world” a therapeutic dose in one patient might not be adequate in another. If patients have widely varying body weights, the amount of drug each receives (on a mg to mg basis) could vary widely.

10. Therapeutic Concentration  For many drugs there is no proven exact correlation between the concentration of the drug and clinical response. Beta blockers- propranolol, metoprolol anti-inflammatories- ibuprofen, naprosyn Some antidepressants- Paxil, Celexa, Zoloft Cholesterol/Triglyceride lowering agents- Clonidine (BP), Ketoconazole (antifungal)

11. Therapeutic Concentration  For many, it is easier and more clinically relevant to measure the response, or another marker Warfarin- PT/ INR, Heparin- PTT Cholesterol lowering drugs- blood cholesterol Diuretics (Dyazide, Diuril)- urinary output Anti-diabetic drugs (actos, miglitol, Glipizide, glucotrol, metformin)- blood glucose Antibiotics (PCN, TCN, Ery., keflex)- blood bacteria levels

12. Therapeutic Concentration  For some drugs, assaying levels is expensive or inconvenient Free phenytoin levels vs. bound phenytoin levels  Drug concentrations can be used to help indicate whether or not the patient has been compliant with medication regimen BUT, no guarantee of compliance with regimen.

13. Therapeutic Range  If drug has a therapeutic range, then doses should be employed which will assist patients achieving concentrations in the therapeutic range  Drugs with narrow therapeutic ranges: Digoxin, Lithium, Dilantin, Theophylline, Tegretol, Vancomycin, Gentamicin, Tobramycin, Procainamide, Lidocaine, Quinidine

14. Pharmacokinetic Properties  Absorption: Efficacy measurements taken at appropriate times, ie. after absorption  Bioavailability can be altered by: Concomitant ingestion of food- antibiotics Diurnal variation- pravastatin, prednisone Alterations in GI tract motility- Reglan (ac) pH differences- enteric coated: ASA, bisacodyl

15. Absorption in relation to meals  Pen VK with food slows rate but not overall absorption  Pen G has decreased absorption w/ food  Ketoconazole has increased absorption w/ food  Griseofulvin absorption is increased w/ high fat meal.

16. Onset of Action  Immediate release tablet/capsule has fast onset  Delayed release has slower onset  Liquids have fast onset  Injectables have fastest onset  Transdermal patches have slow onset

17. Time Until Onset of Effect Differences  Nicotine patch- 2-4 hrs  Clonidine patch - 6-12 hrs  Duragesic patch 8-12 hrs

18. Timing of Dose in Relation to Blood Levels  Antibiotics should be dosed around the clock for maximum bioavailability  Gentamicin is renal toxic if levels are not allowed to drop before re-dosing  Nitrates need to have blood levels drop to a drug free period to be most effective

19. Time To Therapeutic Effect  Need blood levels drawn at appropriate time  Dependent on half life of drug  Steady state achieved w/in 4-5 half lives  Takes 4-5 half lives to remove drug from body  Peak and/or trough blood levels are appropriate for some toxic drugs (Gentamicin, Vancomycin, Tobramycin)

20. Concurrent Medications  Subjects may take non study drugs: because they have another medical condition if they were taking them before this study began.  Consider drug interactions with study med increase bioavailability may make study drug look more effective than it is affect underlying disease state being studied taken equiv. amounts in tx and control group? Do they contribute to adverse effects observed?

21. Study Setting- Inpatient Setting  The more rigidly controlled the environment is, the more difficult to extrapolate the findings to the outside population  Inpatient close supervision - improved compliance less exercise/ activity - more tests needed more evaluations needed - less protocol variation less protocol variation less environmental variability

22. Outpatient Setting  More environment variability  Less compliance control  More diet variability  Less testing  less supervision  more protocol variation

23. Artificial Setting  Arranged environment (NH, VA hospital, clinical research labs, dorms, hotel rooms, prisons)  Used more often in studies which recruit volunteers.  This environment is primarily used to control a greater # of variables

24. Compliance of Drugs  “80% of patients take less than 80% of their prescribed doses”  Those with mild disease have worst compliance  Those with severe disease have moderate compliance  Those with moderate disease have best compliance

25. Compliance Bias  Occurs when differences in tx lead to different degrees of compliance by patient  Bias exists when it can be concluded that one of the drugs lacked efficacy when in actuality, it might not have been taken.  Example: Using Nitroglycerin oint vs. patch  Ointment messy, more frequent applications  Patch once per day at bedtime (easier)  Compliance is usually a greater concern in studies involving out-patients than in-patients

26. Methods to Measure and Assess Compliance  Observing patients take their doses  pill counts  use of a non-toxic inert marker in study med  asking the patient directly and frequently  measuring the concentration of drug in blood stream  use of an electronic device in the vial cap  review of Rx records- refills, patient diaries  Physiological evidence- HR, BP, urine color

27. How Can Non-Compliance Effect the Study Results  A drugs therapeutic response will be less than expected or absent  A drug will be considered less potent than it actually is  One drug could be assumed to be similar or less effective than another drug  Non-compliance increases the sample size needed to detect a difference between groups

28. How to Analyze Non- Compliance  Exclusion: Drop non-compliant patients from evaluation of the results.  Intent-to-treat :Include everyone even if they had their therapy altered (non-compliant) taking patients last score at time they dropped out taking average score for entire group taking worst score for entire group

29. Number Needed to Treat (NNT)  NNT: number of individuals that need to be treated in order to prevent one adverse event or one outcome. NNT = 1  ARR  Ex: study determine efficacy of drug preventing cancer. Incidence of cancer in placebo 15%, in treatment group 5%  15%-5% = 10% 1/10% = 10=NNT (10 pts needed to treat to prevent 1 case of cancer  NNT= 1/ placebo - treatment group

30. Number Needed to Harm (NNH)  NNH= 1/ treatment- placebo group  Ex: Headache occurred in 25% of placebo patients and 75% of patients taking drug X.  The NNH = 75%-25% = 50% 1/0.5 = 2  Only 2 patients would need to be treated with drug X in order to cause a headache occurrence.