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Abstract Number: 1979

Care Gap in the Treatment of Patients with High Risk for Fractures in a Single Canadian Academic Center

Arthur N. Lau1, Michael Branch2, Robert Bensen3, Jonathan D. Adachi4, Alexandra Papaioannou5, William Wong-Pack6 and William G. Bensen7, 1Rheumatology and Clinical Epidemiology, Division of Rheumatology, McMaster University, Hamilton, ON, Canada, 2CEO, Inovex, Oakville, ON, Canada, 3Rheumatology Health Team, Dr. Bensen's Rheumatology Clinic, Hamilton, ON, Canada, 4St Joseph's Healthcare Hamilton, Hamilton, ON, Canada, 5Geriatric Medicine, McMaster University, Hamilton, ON, Canada, 6Department Of Nuclear Medicine, Hamilton, ON, Canada, 7Department of Medicine, Division of Rheumatology, St. Joseph's Hospital and McMaster University, Hamilton, ON, Canada

Meeting: 2012 ACR/ARHP Annual Meeting

Keywords: Bone density, fractures and osteoporosis

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Session Information

Title: Osteoporosis and Metabolic Bone Disease

Session Type: Abstract Submissions (ACR)

Background/Purpose:

A number of clinical prediction tools are available to stratify patients into low, moderate and high risk for fractures in future. These tools are valuable in determining which patients should be initiated on an anti-resorptive agent. Bone Destiny is a validated tool which can accurately predict a patient’s 10 year fracture risk. Patients are stratified into colours (green, yellow, orange, red and purple) which range from low to high 10 year risk. Patients in the purple and red range are deemed to be at very high and high risk respectively (10 year fracture risk >20%), and should be treated with an anti-resorptive agent. The goal of this study is to assess if a care gap exists in patients deemed at high risk of fractures using the Bone Destiny tool, and also if a similar gap exists in patients with a T-score in the osteoporosis range.

Methods:

At a large single academic center in Hamilton, Canada, all patients who received a BMD from May 1, 2011 to April 30, 2012 were assessed using the Bone Destiny assessment tool and assigned a colour according to their fracture risk.  All prevalent fragility fractures were recorded. We also assessed for the percentage of patients in each colour group being treated with either Prolia, Actonel, Fosavance, Evista, Aclasta or Forteo.

Results:

At our center, 26,213 patients received a DXA scan and a Bone Destiny assessment. 3,643 patients were in the purple group, 4,501 patients were in the red group. Overall, 1805/3643 (49.5%) patients in the purple group and only 1817/4501 (40.4%) patients in the red group were on treatment. The younger patients (age<60 years) in the purple group were less likely to be started on treatment compared to older patients in this group (32.5% in age<60 years, while 46.1% in age 60-69 years, 53.9% in age 70-79 years, and 51.7% in age>80 years). The same trend was seen in the patients in the red group, where 32.9% of patients <60 years were on treatment, 41.4% in age 60-69 years, 44.3% in age 70-79 years, and 41.4% in age>80 years.

When we sorted patients in the database based on BMD T-scores, we found 3,367 patients with a T-score between -2.5 to -3.0. Only 1579/3367 (46.9%) patients were being treated with one of the listed agents. A similar trend was noticed, as younger patients were less likely to be on appropriate therapy. Only 33.8% of patients with age<60 years were on treatment, compared with 46.5% in age 60-69 years, 53.6% in age 70-79 years, and 53.7% in age>80 years.

Conclusion:

It is important for clinicians to use a risk assessment tool to predict which patients are at high risk for fractures and start them on appropriate treatment. At our center; only 49.5% of patients in the purple group were on appropriate treatment and only 40.4% of patients in the red group. This is quite alarming, as the 67% (2443/3643) of patients in the purple group, and 33.4% (1502/4501) in the red group have a prevalent fragility fracture. This study suggests that a care gap indeed exists in patients at high risk for fractures, despite having the Bone Destiny tool to identify which patients require treatment. These results suggest more education is required to educate physicians and other healthcare providers about the availability and usefulness of such tools.


Disclosure:

A. N. Lau,
None;

M. Branch,
None;

R. Bensen,
None;

J. D. Adachi,

Amgen, Eli Lilly, GSK, Merck, Novartis, Procter & Gamble, Roche, Sanofi Aventis,

2,

Amgen, Eli Lilly, GSK, Merck, Novartis, Procter & Gamble, Roche, Sanofi Aventis, Warner Chilcott,

5,

Amgen, Eli Lilly, GSK, Merck, Novartis, Procter & Gamble, Roche, Sanofi Aventis, Warner Chilcott,

8;

A. Papaioannou,
None;

W. Wong-Pack,
None;

W. G. Bensen,

Abbott, Amgen, AstraZeneca, BMS, Merck-Schering, Janssen, Lilly, Novartis, Pfizer and Wyeth, Proctor and Gamble, Roche, Sanofi-Aventis, Servier, UCB, Warner Chilcott,

2,

Abbott, Amgen, AstraZeneca, BMS, Merck-Schering, Janssen, Lilly, Novartis, Pfizer and Wyeth, Proctor and Gamble, Roche, Sanofi-Aventis, Servier, UCB, Warner Chilcott,

5,

Abbott, Amgen, AstraZeneca, BMS, Merck-Schering, Janssen, Lilly, Novartis, Pfizer and Wyeth, Proctor and Gamble, Roche, Sanofi-Aventis, Servier, UCB, Warner Chilcott,

8.

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