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1 Aaron M Tejani Vijaya Musini Ken Bassett Patricia Fortin Therapeutics Initiative, UBC Fraser Health Pharmacy Services, BC For a copy of slides please aaron.tejani@fraserhealth.ca

2 Income sources 1% Fraser Health Pharmacy Services 2% per week Therapeutics Initiative, UBC 8% per week FH Pharmacy Services No financial associations with the pharmaceutical industry in 6 years No gifts, honorariums, dinners, lunches, pens, mugs, money, grants, coffee, stocks Deliberate decision Because I have a bias blind spot Promotion affects me at a subconscious level

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4 My mentors and team members:

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6 Think about what outcomes are important to you/patients before you read the research Develop your own hierarchy of important health outcomes Descending order of importance Death, serious adverse events at the top Always look for harm Surrogate outcomes at the bottom

7 All really bad things Definition: results in death, is life-threatening requires inpatient hospitalization or prolongation of existing hospitalization results in persistent or significant disability/incapacity, or is a congenital anomaly/birth defect.

8 The researcher must provide monitoring information to the committee, especially information about any serious adverse events.

9 All serious adverse events (SAEs) should be reported immediately to the sponsor except for those SAEs that the protocol or other document (e.g., Investigator s Brochure) identifies as not needing immediate reporting. The immediate reports should be followed promptly by detailed, written reports.

10 The What net is worth my net of worth? the drugs cannot be assessed by ONLY $5 car looking at primary outcome events and $5 anticipated in my savings adverse account events My net worth: $1, in the black You What need else to do consider you need assets to know? AND debts $5 credit card debt $5 gambling debt $12, mortgage Expected/unexpected adverse events SAEs that are primary outcome measures as What well is my net worth now? $12, in the red

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12 Should be easy right? Regulators and REBs require SAE monitoring All investigators have the data Trials are inherently powered for this outcome We should be allowed to know about the really bad stuff that happens to patients Have to assume it is due to study drugs due to RCT design

13 Study or Subgroup Arbeit 981 Arbeit 991 B8B-MC-AVAE/B8B-AW-AVAG B8B-MC-AVAM DAP-BAC-983 Fowler 26 Katz 28 Nabor 24 Pertel 5 Pertel 8 Pertel 29 Total (95% CI) Total events 372 Heterogeneity: Chi² = 7.84, df = 5 (P =.17); I² = 36% Test for overall effect: Z =.9 (P =.37) Daptomycin Other antibiotic Risk Ratio Risk Ratio Events Total Events Total Weight M-H, Fixed, 95% CI M-H, Fixed, 95% CI Clinical cure Relative risk 1.24 [.87, 1.76] % 32.9% 13.5% 6.7% 6.5% 1.12 [.91, 1.38].91 [.74, 1.11] Not estimable Not estimable Not estimable 1.9 [.8, 1.47] 1.5 [1.8, 2.8] 1.1 [.77, 1.33] Not estimable No significant difference This guy will tell you Use Daptomycin because it Not estimable 12.9% 1. [.89, 1.12] 84 cures 1.% 1.5 infections [.95, 1.16] like all other antibiotics Favours Daptomycin Favours other antibiotic These guys don t emphasize SAE data that they have

14 Study or Subgroup We investigated further: Arbeit 981 Arbeit 991 B8B-MC-AVAE/B8B-AW-AVAG B8B-MC-AVAM DAP-BAC-983 Fowler 26 Katz 28 Nabor 24 Pertel 5 Pertel 8 Pertel 29 Asked company for details on SAE for all trials Daptomycin Other antibiotic Risk Difference Risk Difference Events Total Serious Events adverse Total Weight events M-H, Fixed, 95% CI M-H, Fixed, 95% CI % 19.7% 5.7% 3.5% 2.5% 8.3% 3.5% 2.4% 25.1% 7.1% 3.5%. [-.6,.6].4 [-.1,.8]. [-.8,.8].7 [.,.13].5 [-.17,.26].7 [-.6,.2]. [-.4,.4]. [-.8,.8].4 [-.1,.8].11 [.2,.2]. [-.5,.5] Absolute risk increase.3 [.1,.6] Not provided Significant 3% absolute risk increase for daptomycin versus other antibiotics Used FDA reports to look at SAE details for some NET trials WORTH = HARMFUL Because we imposed our hierarchy Signals for increased cardiac and renal SAE We made sure we looked for SAE data Maybe related to Daptomycin s Total (95% CI) %.3 [.1,.6] We uncovered Total events ability 221 to increase overall 154 CPK net (ie harm the drug Heterogeneity: DESPITE Chi² = 11.28, df may = 1 (P =.34); cause clinical I² = 11% muscle cure rates breakdown) that were.25.5 Test for overall effect: Z = 2.92 (P =.4) Favours Daptomycin Favours other antibiotic similar to other antibiotics Can t do a proper analysis as all details are not available

15 Serious harm data was not in the published reports Net worth = harmful Only because we/fda looked for this SAE data Trials emphasize endoscopic ulcers These are not necessarily clinical ulcers patients would feel

16 Discordance in the messages COX-2 less likely to cause GI toxicity versus NSAIDS COX-2 increase the risk of serious harm versus other NSAIDs COX-2 do not reduce the risk of complicated ulcers versus other NSAIDs

17 Be active, not passive Don t focus only on primary outcome measures in trials Impose a hierarchy of outcomes Allows assessment of net worth of drugs Allows thorough assessment of harm This is typically under-emphasized in trial publications If the published data doesn t answer the question, keep looking! Actively seek serious adverse event data

18 It is error only, and not truth, that shrinks from inquiry. Thomas Paine For a copy of slides please aaron.tejani@fraserhealth.ca