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Example: Clinical effectiveness

Example: Clinical effectiveness. Improvements in long-term mortality after myocardial infarction and increased use of cardiovascular drugs after discharge: a 10-year trend analysis Soko Setoguchi, Robert J Glynn, Jerry Avorn, Murray A Mittleman, Raisa Levin, Wolfgang C Winkelmayer

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Example: Clinical effectiveness

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  1. Example: Clinical effectiveness Improvements in long-term mortality after myocardial infarction and increased use of cardiovascular drugs after discharge: a 10-year trend analysis Soko Setoguchi, Robert J Glynn, Jerry Avorn, Murray A Mittleman, Raisa Levin, Wolfgang C Winkelmayer J Am Coll Cariolol. 2008 51:1255-7

  2. Objective and analysis issues Objective: Assess the relationship between increasing use of cardiovascular medications and trends in long-term prognosis after myocardial infarction (MI) in the elderly • Design/analytic issues • Defining ‘CV drug use’ • Start of follow-up • Avoid immortal person time bias

  3. Potential explanations of improving survival over time

  4. Defining CV Drug Use • Started recommend meds during hospitalization • Filled prescription after discharge • What timing? • Continued to take the medications for a certain period • What if some patients took it every day vs. others skipped them once in a while?

  5. Defining CV Drug Use • Dictate hypothesis clearly would help • Increasing initiation of recommended CV meds during acute hospitalization improved prognosis in elderly patients after MI • Increasing initiation of recommended CV meds in outpatient setting …… • Increasing ‘continued use’ of recommended CV meds in outpatient setting ……..

  6. Defining CV Drug Use • Things to consider in addition to choosing sound hypothesis • Availability of information • No inpatient drug use available • Aspirin use is not fully captured • Sample size • Lose more patients as you assess drug use over longer period

  7. When to start the follow-up for an outcome? • Immortal person time bias • Increasing initiation of recommended CV meds during acute hospitalization improved prognosis in elderly patients after MI

  8. Immortal Person-time Bias • Comparing survival of responders vs. non-responders to a chemotherapy • Usual method • Categorize patients into responders vs. non-responders based on tumor response • Compare survival from the start of the treatment • Length of survival affect the response Anderson J Clin Onc 1983

  9. Immortal-person time bias: example • 1st response evaluated at 2 months after chemotherapy • All patients who died before the 1st evaluation categorized as ‘non-responders’ • Survival was from the time of chemo to 1 year. • 2 month ‘guarantee’ time for all responders Anderson J Clin Onc 1983

  10. Immortal person time bias Suissa PDS 2007

  11. Landmark Method (Analysis) • Landmark Method (Analysis) • ‘Select some fixed time after initiation of therapy as a landmark for conducting analysis’ • = starting follow-up after completion of exposure assessment • Limitations • Results may differ depending on which landmark is chosen • Loss of power • Cannot observe the entire hazard function Anderson J Clin Onc 1983

  12. Study setup • All patients admitted to a hospital with MI (1995 -2004) using algorithm previously shown to have high accuracy (PPV of 94%) • All study patients survived at least 30 days after discharge from the index MI hospitalization • Long-term survival was observed from the 31st day after discharge to the date of death • Assessed • Trend in mortality • Trend in CV drug use (filled prescription within 30 days after discharge) • Trend in PCI during MI hospitalization • Assessed contribution of increasing CV drug use by sequentially including terms for the multivariate model

  13. Time Trends of Treatment for MI Of 21,484 MI patients, 12,142 died during an average follow-up of 3.5 years. A trend towards increasing age and greater prevalence of comorbidities such as hypertension, peripheral vascular diseases, cerebrovascular diseases, diabetes, and chronic kidney disease was observed The use of percutaneous coronary interventions increased over time, whereas use of thrombolytic therapy decreased (Top) Use of all study drugs also increased over time. (Bottom)

  14. Potential explanations of improving survival over time

  15. Improving Trend of Long-term Prognosis for MI

  16. Improving Trend of Long-term Prognosis for MI Disappeared after Adjusting for the Recommended Cardiovascular Drug Use

  17. Use of CV Procedures Did Not Eliminated the Calendar Year Effect Completely

  18. Lessons learned • The criteria for diagnosing MI have changed over the decade studied • likely resulting in an increasing fraction of patients having non-ST elevation MI (NSTEMI). • Unlikely to explain the findings completely. • No information on aspirin use and life style modification. • Studies suggest that use of aspirin is relatively stable after 1995 • unclear whether lifestyle has changed over time in the elderly population • Further investigation is necessary to elucidate the relative and individual contributions of these factors.

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