可預測骨質疏鬆骨折的新演算方法


  【24drs.com】November 24, 2009 — 根據發表於11月19日線上第一版BMJ期刊的新報告,兩種新的演算方法可以在一線照護機構預測骨質疏鬆骨折,無需實驗室測量,將有助於區別可受益於降低風險介入方法的高風險病患。
  
  英國諾丁罕大學的Julia Hippisley-Cox醫師和Carol Coupland醫師寫道,骨質疏鬆骨折是人們一個嚴重且增加中的發病原因,也是健康照護上的一個負擔因素;尤其是髖骨骨折,會相當疼痛、喪失功能、住院,對醫師、病患和公衛而言,需優先加以預防。現在的挑戰是,改善準確區別可受益於降低風險之治療或預防方法的高風險病患。
  
  【發展兩種新的演算方法】
  為此,研究者發展和確定兩種新的骨折風險演算方法,稱之為「QFractureScores」,以該數值估計一個人的10年骨質疏鬆或髖骨骨折風險。
  
  他們也比較新演算方法和目前使用的骨折風險評估(FRAX)演算法,包括了年紀、性別、身高、體重、之前的骨折、雙親髖骨骨折病史、目前有抽菸、使用糖皮質素治療、類風濕性關節炎、次級骨質疏鬆、每天喝酒3杯以上。
  
  作者們解釋,另一種版本的FRAX包括以骨密度測量評估骨折風險,但是並未用來比較。
  
  在建立QfractureScores時,作者們從英格蘭和威爾斯的357間一般開業診所,蒐集15年間、年紀在30-85歲的1,183,663名婦女和1,174,232名男性資料,紀錄偶發骨質疏鬆骨折(脊椎、遠端橈骨、或髖骨)和偶發髖骨骨折的診斷。
  
  女性共有24,350例偶發骨質疏鬆骨折診斷,男性有7,934例;女性有9,302例偶發髖骨骨折診斷,男性有5,424例。
  
  【骨折風險】
  資料顯示,男性的骨折風險因素為年紀、身體質量指數、抽菸狀態、飲酒、類風濕性關節炎、心血管疾病、第2型糖尿病、氣喘、使用三環抗憂鬱藥物、跌倒過、肝病;這些變項都包括在QfractureScores演算方法中。
  
  女性的骨折風險因素為使用荷爾蒙替代療法、抽菸狀態、飲酒、雙親髖骨骨折病史、類風濕性關節炎、心血管疾病、第2型糖尿病、氣喘、使用三環抗憂鬱藥物、使用皮質類固醇、跌倒過、停經症候群、慢性肝病、胃腸道吸收不良、其他內分泌異常、年紀、身體質量指數;這些變項都包括在QfractureScores演算方法中。
  
  作者們寫道,QfractureScore用於估計骨質疏鬆骨折和髖骨骨折的10年絕對風險,與FRAX演算法相比,顯示可改善區別和分級。
  
  這個新演算法擴大年紀範圍,且納入FRAX未包括的其他風險因素,包括跌倒、第2型糖尿病、心血管疾病、使用荷爾蒙替代療法、停經症候群、使用三環抗憂鬱藥物。
  
  他們指出,新演算法的一個優點是,不需要實驗室檢查或臨床測量。
  
  該研究也提供和各類型荷爾蒙替代療法與劑量之相關風險的資訊。減少不抗衡雌激素的風險後,荷爾蒙替代療法有整體保護效果,相較於單純髖骨骨折,併有脊椎、遠端橈骨和髖骨骨折更明顯。作者們指出,這些發現與婦女健康促進研究及其他研究結果一致。
  
  QfractureScore在一般開業機構獲得確認,對於它的發展並無貢獻資料,作者們寫道,它有「好的區別力」或分辨後續有骨折風險病患的能力。
  
  【一些限制】
  他們指出,研究限制是,同樣的電腦系統提供資料用於演算,可能有點太過樂觀,此外,某些病患缺乏關於喝酒、抽菸狀態或身體質量指數的資料,可能造成分類上的錯誤。
  
  作者們結論表示,需要在可能使用的機構對一群獨立樣本進行後續確認研究,以檢測這個新演算法的效果。
  
  EMIS 醫療主任、David Stables資助本研究,作為一個荷爾蒙替代治療之風險與利益評估大型研究的一部份。Hippisley-Cox醫師曾經是QResearch的共同負責人,Qresearch是一個非營利組織,與諾丁罕大學和EMIS有合作關係,她也是ClinRisk的主任,ClinRisk是電腦系統使用的臨床風險演算軟體製造商。
  
  BMJ. 線上發表於2009年11月19日。

New Algorithm Predicts Osteoporotic Fractures

By Fran Lowry
Medscape Medical News

November 24, 2009 — Two new algorithms can predict the risk for osteoporotic fracture in a primary care setting without the need for laboratory measurements and will help identify patients at high risk who could benefit from risk-reducing interventions, according to a new report published in the November 19 Online First issue of the BMJ.

"Osteoporotic fractures are a major and increasing cause of morbidity in the population and a considerable burden to health services. Hip fractures, in particular, result in considerable pain, loss of function, and admission to hospital, making prevention a high priority for patients and physicians and for public health," write Julia Hippisley-Cox, MD, and Carol Coupland, MD, from the University of Nottingham, Nottingham, United Kingdom. "The challenge now is to improve methods for accurate identification of individuals at high risk who might benefit from a therapeutic or preventive intervention."

Two New Algorithms Developed

To that end, the investigators developed and validated 2 new fracture risk algorithms, called QFractureScores, for their value in estimating an individual's 10-year risk for osteoporotic or hip fracture.

They also compared the performance of the new algorithms vs the established fracture risk assessment (FRAX) algorithm, which includes age, sex, height, weight, previous fracture, parental history of hip fracture, current smoking, glucocorticoid treatment, rheumatoid arthritis, secondary osteoporosis, and 3 or more units of alcohol per day.

Another version of the FRAX includes bone mineral density measurements in the assessment of fracture risk, but this was not used as a comparator, the authors explain.

In building the QFractureScores, the authors collected data from 357 general practices in England and Wales on 1,183,663 women and 1,174,232 men aged 30 to 85 years during a 15-year period and recorded the diagnoses of incident osteoporotic fracture (vertebral, distal radius, or hip) and incident hip fracture.

There were 24,350 incident diagnoses of osteoporotic fracture in women and 7934 in men and 9302 incident diagnoses of hip fracture in women, and 5424 in men.

Risk Factors Shown

The data showed that the risk factors for fracture in men were age, body mass index, smoking status, alcohol use, rheumatoid arthritis, cardiovascular disease, type 2 diabetes, asthma, use of tricyclic antidepressants, history of falls, and liver disease. These variables were included in the QFractureScores algorithm.

The risk factors for fracture in women were the use of hormone replacement therapy, smoking status, use of alcohol, parental history of osteoporosis, rheumatoid arthritis, cardiovascular disease, type 2 diabetes, asthma, tricyclic antidepressants, use of corticosteroids, history of falls, menopausal symptoms, chronic liver disease, gastrointestinal tract malabsorption and other endocrine disorders, age, and body mass index. These factors were included in the QFractureScores algorithm.

The QFractureScore for estimating the 10-year absolute risk for osteoporotic fracture and hip fracture shows some evidence of improved discrimination and calibration vs the FRAX algorithm, the authors write.

It extends the age range and quantifies additional risk factors not fully taken into account by FRAX, including falls, type 2 diabetes, cardiovascular disease, use of hormone replacement therapy, menopausal symptoms, and use of tricyclic antidepressants.

An advantage of the new algorithm is that it does not require laboratory testing or clinical measurements, they add.

The study also provides information on risks associated with different types and doses of hormone replacement therapy. There was an overall protective effect of hormone replacement therapy with a decreased risk with unopposed estrogen, which was more marked for vertebral, distal radial, and hip fractures combined vs hip fracture alone. These findings are consistent with those from the Women's Health Initiative and other studies, the authors point out.

The QFractureScore was validated in general medical practices that did not contribute data to its development. The authors write that it had "good discrimination" or the ability to distinguish patients who subsequently had a fracture from those who did not.

Some Limitations

A limitation was that it used the same computer system that provided the information for the algorithm and so might contain "a degree of overoptimism," they note. In addition, missing values for alcohol use, body mass index, or smoking status for some of the patients might have led to some misclassification.

The authors conclude that further validation studies are needed to test the performance of the algorithms in independent populations in settings where they are likely to be used.

This study was funded by David Stables, medical director of EMIS, as part of a larger study examining risks and benefits of hormone replacement therapy. Dr. Hippisley-Cox has been codirector of QResearch, a not-for-profit organization that is a joint partnership between the University of Nottingham and EMIS. She is also director of ClinRisk, a producer of software that implements clinical risk algorithms within computer systems.

BMJ. Published online November 19, 2009.

    
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