Consequences Of Non-Compliance To Osteoporosis MedicationAmong Osteoporotic Women

Ankita Modi, Ph.D, M.D.1, Jackson Tang, M.Sc.2, Shuvayu Sen, Ph.D.1

1Health Outcomes, Merck & Co., NJ, 2AsclepiusJT LLC, NY

Table 1. Patient characteristics in the Baseline period

Conclusions• Rate of non-compliance was found to be high in a managed care population with

osteoporosis. As a result, rate of osteoporotic fractures and healthcare utilization was substantially higher for patients who were non-compliant.

• The results emphasize the importance of good treatment compliance in order to achieve a treatment benefit and thereby reduce the burden that osteoporosis and associated fractures place on individuals and healthcare systems.

Introduction• More than 40 million people in the US have osteoporosis (OP) or are at risk

for developing OP, placing them at greater risk of bone fractures.• Poor compliance with osteoporosis treatment regimens is a well-recognized

problem, and the risk of having osteoporotic-related fractures increases among patients with poor compliance.

• Higher medical costs is also a consequence of poor compliance.

Objective• To examine consequences associated with non-compliance to osteoporosis

(OP) medication in terms of fracture rates and healthcare resource utilization

MethodsStudy design

• A retrospective cohort study was conducted using i3 Invision Datamart; a large U.S. claims database records from January 1, 2001 to December 31, 2010 (study window).

• Index date: The date of initiation of first OP medication (alendronate, ibandronate, risedronate, zoledronate, raloxifene, calcitonin, teriparitide) during the study window.

• Compliance: Defined as having a medication possession ratio (MPR) > 0.8MPR was defined as the total number of days’ supply of all OP mediation

received in the compliance period, divided by 365 days. • Study outcome: OP-related fractures and healthcare resource utilization

OP-related fractures: included non-traumatic fractures occurred at the hip, vertebral, and non-vertebral sites.

Healthcare resource utilization: Medical (Inpatient, Outpatient, ER, and Other) and Pharmacy

• Study period: Consisted of three consecutive, one-year time periods (Figure 1):Baseline period: 1 year prior to the index dateCompliance period: Year 1 after index date, during which compliance with

osteoporosis treatment was calculated Study period: Year 2 after index date, during which study outcomes were

measured• Disease diagnoses and comorbidities were identified based on ICD-9 codes,

medications were identified based on NDC codes.

Study sample• Inclusion:

Prescribed with > 1 OP mediation in the study windowFemale aged > 55 as of index date> 12 months pre- and > 24 months post-index continuous eligibility

• Exclusion:Paget’s disease ever in the claims historyDiagnosis of malignant neoplasm during the study period

Data analysis• Baseline period: patient characteristics• Study period:

OP-related fractures• Fracture rates (% of patients with fractures), by fracture type

All-cause and OP-related health care resourceOP-related health care eventsMultivariate analysis

• Key independent variable: non-compliance (MPR < 0.8)• Covariates: Age, presence of GI symptoms at baseline, OP-related

fractures at baseline, CCI, and presence of other comorbidities at baseline

• Fracture rates: Logistic regression • All-cause resource utilization (Yes/No): Logistic regression • All-cause number of resource use: Gamma regression

Presented at The DIA 2013 49th Annual Meeting, Boston, MA, June 22 – June 27, 2013.

Poster Session IID: 52370

MPR calculated

Study period(12-months)

Baseline period(12-months)

Compliance period

(12-months)

OP-related fractures and

resource utilization assessment

Index DateInitiation of OP

medication

 

Naive to all osteoporosis treatment

Figure 1. Study period Results• Among 57,913 women who met eligibility criteria, 34,483 (59.5%) were

non-compliant to osteoporosis therapy during year 1 (mean [SD] age, 64.2 [8.9] years). (Table 1)

• Non-compliant patients also experienced significantly more hospitalization events (12.3% vs. 9.6%), emergency room (ER) events (12.4% vs. 11.1%) and frequent OP-related hospital stays (0.03 vs. 0.02) during year 2 (all p<0.01). (Table 2)

• Compared to compliant patients (N=23,430 (40.5%)), a significantly higher proportion of non-compliant patients developed vertebral (0.79% vs. 0.48%), hip (0.42% vs. 0.25%) and non-vertebral (1.93% vs.1.52%) fractures during year 2. (Table 3)

N = 686,505

Patients initiating OP treatmentThe initiation of the first BIS is defined as the Index Date

N= 488,361

Female age > 55 as of index date

N = 87,235

Patients with > 12-month continuous eligibility before and > 24-month of continuous eligibility after the index date

N = 57,913

Exclude patients with malignant neoplasm or Paget’s disease of bone

TOTAL SAMPLE = 57,913

Figure 2. Sample selection 

Compliant(N = 23,430) [40.5%]

Non-compliant(N = 34,483) [59.5%] P-value

Baseline N % N %

Age at index date (mean, std) 63.6 8.5 64.2 8.9 <0.01

Charlson comorbidity index (mean, std) 0.44 0.9 0.56 1.0 <0.01

Baseline fractures 866  3.7% 1,566 4.5% <0.01

Vertebral (dorsal/lumbar) 284 1.2% 533 1.6% 0.01

Hip 142 0.6% 254 0.7% 0.06

Other 579 2.5% 1,021 3.0% <0.01

Baseline medication use

Gastro-protective agents 3,906 16.7% 6,840 19.8% <0.01

Estrogen 6,271 26.8% 7,766 22.5% <0.01

NSAIDS 5,478 23.4% 9,112 26.4% <0.01

Table 3. Study Period Fracture Rates

 Compliant

(N = 23,430) [40.5%]Non-compliant

(N = 34,483) [59.5%] P-valueNumber of Patients with OP-related fractures N % N %

Vertebral (dorsal/lumbar) 113 0.48 273 0.79 <0.01

Hip 58 0.25 145 0.42 0.01

Other 356 1.52 667 1.93 <0.01

Table 2. Study Period Healthcare utilization

 Compliant

(N = 23,430) [40.5%]Non-compliant

(N = 34,483) [59.5%] P-value

Number of patients N % N %

All-cause health care resource

Inpatient 2,256 9.6% 4,236 12.3% <0.01

Emergency room 2,610 11.1% 4,282 12.4% <0.01

Outpatient services 22,525 96.1% 32,548 94.4% <.001

Other medical services 16,046 68.5% 23,513 68.2% 0.45

OP-related health care resource

Inpatient 419 1.8% 713 2.1% 0.017

Emergency room 174 0.7% 280 0.8% 0.35

Outpatient services 7,656 32.7% 9,308 27.0% <0.01

Other medical services 1,585 6.8% 2,083 6.0% <0.001

OP-related health care events mean std mean std

Inpatient 0.02 0.18 0.03 0.22 <0.01

Emergency room 0.01 0.23 0.01 0.17 0.45

Outpatient services 0.69 2.71 0.60 2.37 <0.01

Other medical services 0.13 1.63 0.13 0.97 0.83

 Logistic regression Any fractures Vertebral fractures(lumbar or dorsal)

Hip fractures (femur neck)

  OR 95% CI P-value OR 95% CI P-value OR 95% CI P-valueTreatment non-compliance (MPR< 80%)

1.19(1.06, 1.3)

<0.01 1.43 (1.14, 1.79) <0.01 1.47 (1.08, 2.00) 0.02

 Logistic regression Inpatient use ER use Outpatient useOther health care

resource use  OR 95% CI P-value OR 95% CI P-value OR 95% CI P-value OR 95% CI P-valueTreatment non-compliance (MPR< 80%)

1.16(1.10, 1.23)

<0.01 0.99(0.93, 1.04)

0.74 0.61(0.56, 0.67)

<0.01 0.93(0.90, 0.97)

<0.01

Gamma regressionNumber of Inpatient

eventsNumber of ER events

Number of Outpatient events

Number of other types of resource utilization events

  IRR 95% CI P-value IRR 95% CIP-

valueIRR 95% CI

P-value

IRR 95% CIP-

valueTreatment non-compliance (MPR< 80%)

1.27(1.19, 1.33)

<0.01 1.03(0.95, 1.11)

0.43 0.97(0.95, 0.98)

<0.01 1.10(1.06, 1.14)

<0.01

Multivariate Results• Non-compliance was associated with higher OP-related fractures (Table 4)19%, 43%, and 47% more likely to experience any fractures, vertebral, and hip

fractures, respectively. • Non-compliance was associated with more frequent inpatient events 16% more likely to experience > 1 inpatient visit, 95% CI: [1.10, 1.23] (Table 5)27% more likely to have an additional inpatient event, 95% CI: [1.19, 1.33] (Table 6)

Table 4. Association of Fracture Rates and Treatment non-compliance

Table 5. Association of healthcare resource and Treatment non-compliance

Table 6. Association of healthcare events nd Treatment non-compliance

DisclosureAuthor(s) of this presentation have the following to disclose concerning possible financial or personal relationships with commercial entities that may have a direct or indirect interest in the subject matter of this presentation: • Ankita Modi: Employee – Merck & Co.• Jackson Tang: Consultant – Received research funding from Merck & Co.• Shuvayu Sen: Employee – Merck & Co.