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Re-fracture risk in older patients prescribed bisphosphonates Chiara Sorge Rome, 15th October 2012.

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Presentation on theme: "Re-fracture risk in older patients prescribed bisphosphonates Chiara Sorge Rome, 15th October 2012."— Presentation transcript:

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2 Re-fracture risk in older patients prescribed bisphosphonates Chiara Sorge Rome, 15th October 2012

3 BACKGROUND Osteoporosis and associated fractures: a public health issue of growing importance Almost 9 million osteoporotic fractures every year worldwide Italy has one of highest life expectancies in the world: 79.4 years for males and 84.5 for females In 2010 Italy had the second higher expenditure attributable to fractures in Europe

4 BACKGROUND PREVENTION & TREATMENT Diet, exercise, reduced alcohol consumption, smoking Vitamin D and calcium intake Hormone related therapy Pharmacological treatments –Bisphosphonates –SERM (e.g. raloxifene) –Strontium ranelate –Teraparatide hormone Primary prevention: Secondary prevention: NICE guidelines (2011 update) Aifa nota 79 (2011 update)

5 METHODS To estimate the association between adherence to anti-osteoporotic drug therapy and risk of subsequent fractures OBJECTIVE:

6 METHODS Study population: patients aged 50 years or more discharged from hospital/ER of Lazio region with a diagnosis of a fracture of any bone and prescribed any drugs registered for osteoporosis treatment Study design: nested case-control study Study period: enrolment 2006-2009, 1 year follow-up Exclusion criteria: –Not residents/not in charge of Regional Health System –Previous fractures –Multiple trauma –History of malignancies, Paget’s disease

7 METHODS Data sources:Lazio Health Information Systems –Hospital Information System (HIS) + ER visits –Drug dispensing registry (PHARM) –Health-tax exemption registry –Mortality Information System (MIS)

8 METHODS Cases: patients with a second fracture within 1 year after discharge (excluding the first month) Controls: patients without a second fracture whithin the case follow up time Ratio: 4 controls for each case Matching variables: age, gender and case follow-up time

9 METHODS Exposure: adherence to anti-osteoporotic therapy Measure: proportion of days covered by drug (PDC) PDC=days of treatment/days of follow-up Adherent: PDC≥80% Partially adherent: 20%≤PDC<80% Not adherent: PDC<20%

10 METHODS Assumptions: - prescriptions equals to consumption - patients take drugs at the defined daily dose - patients finish the current fill before starting a new one - subtraction of the total number of days spent in inpatient regimen - for patients already on treatment at enrolment, remaining days from the last prescription were added - truncation of days of utilization that falls after the end of follow-up time

11 METHODS Potential confounders: -chronic medical conditions (rheumatoid arthritis, epilepsy, malabsorption sindromes, diabetes, cardiovascular diseases….) -use of certain drugs (corticosteroids, antidepressants, opioid analgesics….)

12 METHODS 01 Jan 2006 Start of enrolment 31 Dec 2010 End of follow-up 30 days: buffer period Outcome: subsequent first fracture (HIS/EIS) Censoring: mortality (MIS), cancer, Paget’s disease (HIS/EIS) 1 year: drugs use (PHARM) Comorbidities assessment (HIS/EIS/PHARM) 8 years: hospitalizations (HIS/EIS) Follow-up time 1 year Discharge index admission (HIS/EIS)

13 RESULTS 835 cases 3337 controls 191638 patients admitted to hospital/ER for fracture 10722 patients (re-fracture rate: 7.1 per 100pys) Exclusion criteria

14 RESULTS: CHARACTERISTICS OF THE STUDY POPULATION (1) Median follow up time 151 days Baseline characteristics ControlsCases N%N% Age (mean, sd) 74.69.474.79.4 Gender (females) 312093.578093.4 Place of residence Lazio region 160148.037645.0 Rome 173652.045955.0 Fracture site Vertebra 47314.213215.8 Rib 2918.7789.3 Pelvis1043.1344.1 Upper limbs 128038.434941.8 Hip64219.214116.9 Lower limbs49314.89110.9 Other/unspecified 541.6101.2 Admission type E.R. only 175852.737244.6 Hospital admission only57217.121325.5 E.R + hospital admission 100730.225029.9 Exposure PDC <20%98829.626732.0 20-80%123036.931337.5 >80% 111933.525530.5

15 RESULTS: CHARACTERISTICS OF THE STUDY POPULATION (2) * Previous hospitalizations + health tax exemptions

16 RESULTS: CHARACTERISTICS OF THE STUDY POPULATION (3) * at least 2 prescriptions in the year before enrolment

17 RESULTS OF CONDITIONAL LOGISTIC REGRESSION Adherence to anti-osteoporotic therapy seems to decrease re-fracture risk

18 CRITICAL ASPECTS Observational study/Use of administrative database/ Assumptions/ Exposure misclassification: assumptions in PDC calculation, switching to non-oral medications Outcome misclassifcation: fractures not receiving medical attention, recurrences of same fracture Misclassification of covariates: undereporting of chronic conditions in administrative databases, misspecification following combination of different diseases/drugs Residual confounding (BMI, smoking, alcohol consumptions, vitamin D intake, ….)

19 CONCLUSIONS Sub-optimal compliance to osteoporosis treatment Adherence to anti-osteoporotic treatment seems to decrease re-fracture risk Claims data can be used to assess co-morbidities, to evaluate prescribing appropriateness according to international guidelines, treatment effectiveness Future projects Collaboration with orthopaedists and geriatricians of Campus biomedico (Rome): effect of long-term therapy on atypical hip fractures.

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