A Study On Primary Osteoporosis Screening Tool For 40-65 Years Old Women Based On Generalized Partial Linear Model

1 Objective1.1 To screen out important risk factors and TCM syndrome essential factors of primary osteoporosis (POP).1.2 To establish a discriminant model for POP with risk factors and TCM symdrome essential factors based on generalized partial linear model (GPLM), which is a mathematical model for POP screening tools.1.3 To create a POP screening tool for community population in Beijing and Shanghai, so as to provide scientific evidence in detecting person's POP risk.2 Methods2.1 POP risk factors screening questionnaire designIn a previous study, a primary osteoporosis TCM syndromes questionnaire was designed and used. On that basis, we developed the questionnaire on osteoporosis risk factors and TCM syndromes of 40?65 years old community women by referring to scaling methods, clinical epidemiological methods, clinical osteoporosis profession and a national TCM syndromes differentiation guideline. This screening questionnaire is a closed-ended questionnaire included 65 items concerned with 5 aspects:general background information, lifestyle, TCM symptoms and signs, body examination, and other related personal pathogenic factors. Before the survey was conducted, the questionnaire was examined and approved by clinical medical ethics committee of Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences.2.2 Study population2.2.1 Inclusion criteriaInclude women:(1) 40-65 years old; (2) with clear consciousness and reading ability, and good communication with investigators; (3) be willing to accept the questionnaire survey and bone mineral density(BMD) test. 2.2.2 Exclusion criteriaExclude:(1) secondary osteoporosis caused by drugs or other diseases, such as diabetes, suppurative myelitis, nephritis, hyperthyroidism, etc.; (2) malignant tumor, gout, and rheumatoid arthritis which may influence TCM syndromes evaluation; (3) mental disorders or cognitive disabilities.2.3 Diagnostic criteria of POPAccording to the guidelines for diagnosis and treatment of common internal diseases in Chinese medicine:diseases of modern medicine(2008, published by China Association of Chinese Medicine), the minimum T-score of BMD test on lumbar L1?L4, femoral neck, total femur were selected as the index of osteoporosis diagnostic criteria. T-score> M-1SD can be recognized as normal bone mass, M-1SD?2.0SD as osteopenia. and<M-2.0SD as osteoporosis.2.4 Data sourceFrom March to August 2009, women of 40?65 years old with high POP risk factors at three community health service centers in Xuhui district(Shanghai), and five community health service centers in Dongcheng district(Beijing) were selected. And then screening questionnaire survey and bone mineral density(BMD) examination were conducted. In Shanghai, out of 1101 distributed questionnaires,1027 answered questionnaires were collected. After that.26 unqualified questionnaires were excluded,. Finally,1001 qualified questionnaires with a proportion of 90.92% were identified. In Beijing, out of 800 distributed questionnaires,763 answered questionnaires were collected, then 24 unqualified questionnaires were excluded and 739 qualified questionnaires with a proportion of 92.38% were identified finally. All the data were input into a web-based osteoporosis health management system (http://210.76.97.192:8080/gzss) by two researchers independently. Consistency test was done between the two researchers data entry. At the end. electronic data of 1740 qualified questionnaire and BMD test results were collected.2.5 Statistical analysis2.5.1 Statistical analysis softwareSPSS 18.0 for Windows, SAS 9.2 for Windows and SPSS Clementine 12.0 were used for questionnaire data analysis and modeling analysis. Lantern 1.5 package was used for latent tree model analysis.2.5.2 Reliability and validity analysisThe questionnaire's reliability was evaluated with Cronbach coefficient a and Guttman coefficient, and the structural validity of TCM symdromes was evaluated with factor analysis.2.5.2 POP risk factors analysisThe quantitative relation between risk factors and POP was analyzed with multinomial logistic regression, in order to establish a multinomial logit model and screen out risk factors associated with POP.2.5.3 Analysis on basic syndrome factors of POPThe basic POP syndrome factors and their relationships were analysized with latent tree model method.2.5.4 POP discriminant modelA data mining method named Support vector machine (SVM) was used to explore the POP risk factors and TCM symptoms which were combined with the qualitative diagnosis data from BMD test to establish a POP discriminant model based on the GPLM.2.5.5 Evaluating POP screening toolReceiver operating characteristic curve (ROC) was used to evaluate the discriminative accuracy of POP screening tool. Normally, the area under ROC curve (AUC) is a useful index to assess the diagnostic value of screening tools.3 Results3.1 Reliability and validity evaluation of the screening questionnaire3.1.1 Reliability evaluationThe Cronbach coefficient a for the four aspects:kidney yang deficiency syndrome, liver and kidney yin deficiency syndrome, spleen and kidney yang deficiency syndrome and blood stasis syndrome, were 0.803,0.871,0.811 and 0.707 respectively. The total a for the four TCM syndromes was 0.913. The values of the Guttman split-half reliability for the four aspects were 0.789,0.831,0.743 and 0.699 respectively.The total value of Guttman split-half reliability for the four TCM syndromes was 0.867.3.1.2 Validity evaluationFactor analysis was conducted to evaluate the validity. Common factors were extracted after average orthogonal rotation and 25 times rotation by following the principal component method. The KMO test value was 0.935(>0.5), and Bartlett's test value X2 was 18058.066, df=741, P<0.01. According to the criterion of eigenvalues> 1, ten factors were extracted, with a cumulated variance contribution rate 53.789%.3.2 POP risk factors screening3.2.1 Descriptive statistics on POP related factorsThe mean values of age, body mass index (BMI), and duration of menopause among three groups:the normal bone mass group, osteopenia group and osteoporosis group, were statistically different (P<0.05) after variance analysis. The distribution proportion of meat diet, fish diet, coffee, drinking daily exercise time, whether height shorten, whether menopause, previous pregnancy history previous obstetric history and bone fracture history among three groups were statistically different (P<0.05) after crosstab analvsis.3.2.2 Multinomial logit model about POP risk factorsAccording to Alpha level=0.05, six independent variables were calculated in the multinomial logit model, including duration of menopause, body mass index, fish diet, whether height shorten, whether menopause, and previous obstetric history.3.3 TCM syndrome essential factors of POP3.3.1 Descriptive statistics on TCM symptomsIn both study populations in Beijing and Shanghai,19 TCM symptoms,for instance, forgetfulness, pains increase in cold weather, limp aching lumbus and knees, intolerance to heat, fatigue, intolerance to cold, osphyalgia, irascibility, hair loss, anorexia, blurred vision, dizziness, lower limb pains, heavy legs, insomnia, times of nocturia. clear abundant urine, weak legs, back pains, loose teeth, dry eyes, shortness of breath, constipation, many dreams or easy to wake up, lower limb cramps, body pains, tinnitus, night sweat, frequent urination, bitter taste and feverish palms and soles have a frequency rate higher than 15%. Through variance analysis and two independent sample t-test, the incidence of 9 TCM symptoms was statistically different(P< 0.05) between normal bone mass group and osteoporosis group, including intolerance to cold, dry eyes, loose teeth, anorexia, abdominal distention, fullness in the chest and rib-side, times of nocturia, lower limb cramps and lower limb pains.3.3.2 Latent tree model about TCM syndrome essential factors of POPA latent tree model with the highest BIC score-15671 was constructed with heuristic single hill-climbing (HSHC) algorithm. The latent variables showed in the model were consist with the basic TCM syndrome essential factors of POP. including kidney deficiency, liver deficiency, yang deficiency, yin deficiency, kidney essence insufficiency and blood stasis.3.4 Establishment and evaluation of a discriminative model about POP based on GPLM3.4.1 Variables screening for GPLM12 important variables for determining POP were screened out with SVM method based on RBF kernel function, including whether menopause, duration of menopause, fish diet, dry eyes, humpback, body mass index, production times, lower limb cramps, lower limb pains, abdominal distension, fullness in the chest and rib-side, coffee etc.3.4.2 Parameter estimation of GPLMIn the GPLM linear part, coefficients of whether menopause, body mass index, lower limb cramps, lower limb pains and duration of menopause(linear effect) were: 1.14182,-0.15805.0.36149,0.32267,0.12956 respectively, with a statistical significance(P<0.05). In the nonlinear part, duration of menopause (nonlinear effect), X2=13.5948, P=0.0012, with a statistical difference(P<0.05).3.4.3 Evaluating GPLM A linear logistic regression model was fitted with whether menopause, lower limb cramps, lower limb pains and body mass index four risk factors and TCM symptoms as independent variables, and the BMD qualitative diagnosis as dependent variable, with the AUC value 0.7536. The AUC value of GPLM was 0.7971 with the nonlinear effect of duration of menopause. After statistical test, X2 value was 21.9162, P<0.001, with a statistical significance (P<0.05), which indicated that the GPLM model with nonlinear effect was better than the linear logistic regression model.3.5 Establishment and evaluation of the POP screening tool3.5.1 Establishing of the POP screening toolFive factors such as whether menopause, duration of menopause, body mass index, lower limb cramps and lower limb pains were recognized as the main items for the POP screening tool. According to the parameters from GPLM, a mathematical formula of the POP screening tool was formed:Score=31.3×whether menopause+ 11.4×duration of menopause-8.5×body mass index+14.4×lower limb cramps+ 13.8×lower limb pains.3.5.2 Evaluating the POP screening toolAUC value of the POP screening tool was 0.789 (95%CI:0.766 to 0.812). Compared with AUC=0.5. the Z value was 21.482. P<0.0001, with a statistical significance (P<0.01). With the cun-off value-80, the sensitivity of the POP screening tool was 55.67%(95%CI:50.6% to 60.6%), and specificity was 84.62%(95% CI:82.0% to 87.0%), the positive predictive value was 63.0%(95%CI: 57.7% to 68.0%), the negative predictive value was 80.2%(95%CI:77.5% to 82.8%), and Youden index was 0.403. According to the cun-off value-80, out of the high-risk population(Score?-80), osteoporosis group accounted for 63.0% and normal bone mass group accounted for 37.0%. Whereas, for the low-risk population (Score<-80).80.2% were normal bone mass, and only 19.8% were osteoporosis.4 Conclusions4.1 Menopause was a main risk factor for POP, and low body mass index was also a risk factor for POP. A negative correlation exists between POP and fish diet.4.2 Lower limb cramps and lower limb pains are important TCM symptoms for POP. Kidney deficiency, liver deficiency, yang deficiency, yin deficiency, kidney essence insufficiency and blood stasis were the basic TCM syndromes essential factors for POP. Pathological changes of liver and kidney were the main reasons and kidney deficiency was the main syndrome. Latern tree analysis method could avoid the disadvantages of clustering analysis method on TCM syndromes.4.3 Through fit testing the nonparametric part of GPLM model, the nonlinear effect between duration of menopause and POP was found. Western medicine risk factors and TCM symptoms were identified as linear variables, and duration of menopause as nonlinear variables. GPLM had more accurate discriminative characteristics, beng compared with other linear logistic regression models.4.4 TCM syndrome essential facors were added into the previous POP risk screening tool, which has been modified with good sensitivity, specificity and discriminative accuracy on screening high-risk POP population, and could meet the need of TCM clinical application.