Clinical Trial Details
— Status: Completed
Administrative data
| NCT number |
NCT05499403 |
| Other study ID # |
TAILOR |
| Secondary ID |
|
| Status |
Completed |
| Phase |
|
| First received |
|
| Last updated |
|
| Start date |
May 1, 2022 |
| Est. completion date |
February 6, 2024 |
Study information
| Verified date |
March 2024 |
| Source |
Centre Hospitalier Universitaire Vaudois |
| Contact |
n/a |
| Is FDA regulated |
No |
| Health authority |
|
| Study type |
Observational
|
Clinical Trial Summary
Osteoporotic fractures are associated with significant morbidity, increased mortality and
reduction in the quality of life, available treatments reduces the fracture risk between 30
and 70%, however some patients experience a new fracture and/or continue to loose bone during
treatment; this has been defined as treatment failure (TF). The epidemiology and biological
bases of TF are currently under-investigated, thus it is impossible for the physician to
forecast patients' answer to treatment. The aims of TAILOR study are to collect sounded
epidemiological data on TF in a real life setting. To this extent, the investigators will
retrospectively a large cohort of 5000 patients with at least 60 months of anti-osteoporotic
treatment followed in our center for the diagnosis and care of bone metabolic diseases, and
compare TF patients to adequate responders (ARs) for clinical characteristic and biological
parameters. The results will be a "signature" to identify those patients who will experience
TF.
Description:
Fragility fractures represent a major clinical burden in the increasingly older population.
Old suffering with femoral fractures will die within a year (15-25%) or become dependent
(50%). Costs associated with fractures have been estimated to be 32 billion EUR/year in
Europe, 20 billion USD in the United States and 12.5 billion USD in China. The second
fracture worsen the patients' health and increases costs, the financial burden imposed by
second fractures on the United States healthcare system has been calculated in 2 billion
USD/year.
The efficacy of treatment in osteoporosis relies in the reduction of the fracture risk: drugs
approved for osteoporosis reduce the risk of fractures between 30-70% for vertebral
fractures, 40-50% for hip fractures and 15-20% for non-vertebral fractures (1,2). However, no
available treatment reset the fracture risk to zero. Treatment efficacy is assumed by a
significant reduction in fracture risk supported by an increase in bone mineral density (BMD)
and a decrease in markers of bone turnover. The question if a new fracture or bone loss may
be considered a treatment failure is highly debated, recently, a position paper of the
International Osteoporosis Foundation described the treatment failure (TF) based on the
occurrence of two fractures or one fracture plus lack of variation in BMD, markers of bone
turnover or both while on treatment (3).
The study of TF and its prevention is crucial, as the correct and precocious identification
of the patients that will not benefit from the first line drugs, will prevent unsuccessful
treatment and reduce sanitary costs. Several factors has been suggested to be associated with
TF, however, until now, the therapeutic decision relies entirely on physician expertise and
not on decisional algorithms.
The aim of this project is to characterize the clinical characteristics foreseeing TF. The
identification of a signature for TF will increase the standard care of osteoporotic patients
reducing the burden due to a new fracture.
TAILOR will pave the way for the generation of a new algorithm to choose wisely a personalize
therapeutical approach for osteoporotic patients, taking into account their clinical
characteristics, thus minimizing the risk of TF, improving patients quality and expectancy of
life and reducing sanitary costs.
2. Experimental Design and Approach. Retrospective study on patients on treatment with
anti-resorptives or anabolics for primary osteoporosis. All the patients evaluated in the
out-patients service of the unit between 2009 and 2019 (about 5000 subjects) will evaluated,
medical records of patients are available, medical records with missing information will be
excluded.
The investigators will include in the analyses women affected by post-menopausal osteoporosis
treated for at least 12 months and up to 10 years with drugs active on bone turnover and with
at least one follow-up visit in the 10-year period considered. TF will be diagnosed according
to the position paper of the IOF (3): occurrence of two fragility fractures while on
treatment or one fracture plus lack of variation BMD, biochemical markers or both.
Fragility fracture will be defined because of a fall from the standing position or a
mechanical effort without fall. Spinal fractures have be certified by radiography or DXA
morphometry whereas for non-vertebral fractures, a hospital discharge or physician report
will be also considered valid evidence of fracture. Fractures of the skull, face, cervical
spine, fingers, and toes will not be included in our study.
Patients will be considered ARs when they completed 60 months on treatment with no incident
fractures according with Diez-Perez et al. (4), for teriparatide the period considered will
be 24 months.
Patients will be classified according to the type of drug used (SERMs, oral bisphosphonates,
iv bisfosfonates, denosumab or teriparatide), for each patients the following information
will be recorded: age, post-menopausal period, assumption of calcium and vitamin D, presence
and site of fragility fractures, BMD, serum levels of calcium, phosphate, PTH, creatinine,
25OHvitaminD, markers of bone turnover, adverse events. This information will be recorded at
the baseline and at each follow-up visit. The decision of the physician expert in
osteoporosis management during the follow-up visit will be recorded (i.d. continue the
ongoing treatment or change drug, new drugs prescribed).
Patients will be classified as TF based on the occurrence of two fractures while on treatment
or one fracture plus lack of variation in bone mineral density (BMD), biochemical markers or
both(3).
Statistical analyses. The power analysis was conducted using an estimated medium effect size
(f = 0.25), an alpha level of 0.05, and a power of 0.95 using the software G*power. According
to statistical computing, a sample size of n = 400 is required.
The percentage of TF within different treatment and will be compared with AR by means of
ANCOVA for analyzed variables.
the medical decision taken by the physician expert in bone metabolic disorders after
treatment failure (the patient will continue the treatment/switch to another treatment/stop
treatment) will be analysed.
References
1. Body J-J, Bergmann P, Boonen S, Boutsen Y, Devogelaer J-P, Goemaere S, Kaufman J-M,
Rozenberg S, Reginster J-Y. Evidence-based guidelines for the pharmacological treatment
of postmenopausal osteoporosis: a consensus document by the Belgian Bone Club.
Osteoporos Int. 2010 Oct;21(10):1657-80.
2. MacLean C, Newberry S, Maglione M, McMahon M, Ranganath V, Suttorp M, Mojica W, Timmer
M, Alexander A, McNamara M, Desai SB, Zhou A, Chen S, Carter J, Tringale C, Valentine D,
Johnsen B, Grossman J. Systematic review: comparative effectiveness of treatments to
prevent fractures in men and women with low bone density or osteoporosis. Ann Intern
Med. 2008 Feb 5;148(3):197-213.
3. Diez-Perez A, Adachi JD, Agnusdei D, Bilezikian JP, Compston JE, Cummings SR, Eastell R,
Eriksen EF, Gonzalez-Macias J, Liberman UA, Wahl DA, Seeman E, Kanis JA, Cooper C, IOF
CSA Inadequate Responders Working Group. Treatment failure in osteoporosis. Osteoporos
Int. 2012 Dec;23(12):2769-74.
4. Díez-Pérez A, González-Macías J. Inadequate responders to osteoporosis treatment:
proposal for an operational definition. Osteoporos Int. 2008 Nov;19(11):1511-6.
