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Construction of two instruments for the presumptive detection of post-menopausal women with low spinal bone mass by means of clinical risk factors
The objective of this investigation was the design of two instruments based on clinical risk factors for the presumptive detection of post-menopausal women with spinal BMD < 2.5 S.D. below average (LBMD). We investigated the association of 20 risk factors (RF) with LBMD in a series of 131 women....
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| Published in: | Maturitas 2005-07, Vol.51 (3), p.314-324 |
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| creator | Masoni, Ana Morosano, Mario Pezzotto, Stella M. Tomat, Florencia Bentancur, Fabiana Bocanera, Roberto Tozzini, Roberto Puche, Rodolfo C. |
| description | The objective of this investigation was the design of two instruments based on clinical risk factors for the presumptive detection of post-menopausal women with spinal BMD
<
2.5 S.D. below average (LBMD). We investigated the association of 20 risk factors (RF) with LBMD in a series of 131 women. According to current densitometric criteria, subjects were classified as normals (
N
=
33); osteopenics (
N
=
53) and osteoporotics (
N
=
45). Normals and osteopenics were taken as a single group because only ‘nulliparity’ and ‘personal fractures’ exhibited significant differences between these groups. A logistic regression attempting to identify which factors were associated with osteopenia showed a poor fit (pseudo
R
2
=
0.289).
Univariate unconditional logistic regression analysis was used to calculate odd ratios (ORs) and their 95% CI for all RF. Those with associated
P-values |
| doi_str_mv | 10.1016/j.maturitas.2004.08.015 |
| format | article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_67975523</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S0378512204003020</els_id><sourcerecordid>67975523</sourcerecordid><originalsourceid>FETCH-LOGICAL-c399t-ff391443f01b4aeca6866a87ccf4172df9fc0a5f4c989e9e58aecdebad98ab643</originalsourceid><addsrcrecordid>eNqFkcuO1DAQRS0EYpqBXwBvYJdgx3nYy1GLlzQSG1hbjlPWuEns4HKmNb_BF-OmWzNLVqUqn1tl3UvIO85qznj_8VAvJm_JZ4N1w1hbM1kz3j0jOy4HUbWc8-dkx8Qgq443zRV5hXhgjHVMtC_JFe_UINXQ78iffQyY02azj4FGR_MxUv9vtEDISF1MNN8BXRPgtqzZ3wOdIMOjYI2Yq8LG1WxoZnqMpaFHn-_oHI8UVx_KdIwB6GIQ6fhAFzABT1o7--BteU4ef1FnbI4JX5MXzswIby71mvz8_OnH_mt1-_3Lt_3NbWWFUrlyTijetsIxPrYGrOll3xs5WOtaPjSTU84y07nWKqlAQScLNMFoJiXN2Lfimnw4711T_L0BZr14tDDPJkDcUPeDGrquEQUczqBNETGB02vyi0kPmjN9ikMf9GMc-hSHZlKXOIry7eXENi4wPeku_hfg_QUwWHxwyQTr8YnrlRCsOy26OXNQDLn3kDRaD8HC5FOJQk_R__czfwHA07Li</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>67975523</pqid></control><display><type>article</type><title>Construction of two instruments for the presumptive detection of post-menopausal women with low spinal bone mass by means of clinical risk factors</title><source>Elsevier</source><creator>Masoni, Ana ; Morosano, Mario ; Pezzotto, Stella M. ; Tomat, Florencia ; Bentancur, Fabiana ; Bocanera, Roberto ; Tozzini, Roberto ; Puche, Rodolfo C.</creator><creatorcontrib>Masoni, Ana ; Morosano, Mario ; Pezzotto, Stella M. ; Tomat, Florencia ; Bentancur, Fabiana ; Bocanera, Roberto ; Tozzini, Roberto ; Puche, Rodolfo C.</creatorcontrib><description><![CDATA[The objective of this investigation was the design of two instruments based on clinical risk factors for the presumptive detection of post-menopausal women with spinal BMD
<
2.5 S.D. below average (LBMD). We investigated the association of 20 risk factors (RF) with LBMD in a series of 131 women. According to current densitometric criteria, subjects were classified as normals (
N
=
33); osteopenics (
N
=
53) and osteoporotics (
N
=
45). Normals and osteopenics were taken as a single group because only ‘nulliparity’ and ‘personal fractures’ exhibited significant differences between these groups. A logistic regression attempting to identify which factors were associated with osteopenia showed a poor fit (pseudo
R
2
=
0.289).
Univariate unconditional logistic regression analysis was used to calculate odd ratios (ORs) and their 95% CI for all RF. Those with associated
P-values <0.100 were included in a multivariate logistic regression analysis to obtain the odds ratios (OR) adjusted by the effects of the others. The variables with not significant
β coefficients were eliminated, producing a reduced model. BMI (<25
kg/m
2), calcium intake (<1.2
g/day), menopause (>10 years), and the simultaneous occurrence of kyphosis and personal fractures showed significant association with low bone mass at the lumbar spine and their effect was additive. Fitting of the data to the model was assessed with the Hosmer–Lemeshow test (
P
=
0.926) The area under the ROC curve is 0.833 (95% CI
=
0.757–0.909). The following equation calculates the probability of having low spinal bone mass:
ln
P
1
−
P
=
−
3.05
+
1.11
(
>
10
years
of
menopause
)
+
1.19
(
Ca
intake
<
1200
mg
/
day
)
+
2.35
(
BMI
<
25
)
−
0.58
(
personal
fractures
)
+
0.38
(
kyphosis
)
+
2.75
(
personal
fractures
+
kyphosis
)
.
The sensitivity, specificity and area under the ROC curve were defined. The point of maximum specificity and sensitivity derived from the ROC curve, has a probability of 0.409. With such a cut-off point, the equation has a sensitivity of 73%, specificity 79%, positive predictive value 65% and negative predictive value 85%.
The second instrument associates very low lumbar bone mass with the number of risk factors accumulated per patient. At baseline, all subjects had four RFs: they were, women, white, post-menopausal, and with no previous exposure to estrogens. With six additional RFs the presumptive diagnosis of LBMD has a specificity of 99%, positive predicting value 94% and false positives 6.5%. The area under the curve in a ROC graph was 0.826 (95% CI
=
0.747–0.914).
Comparing present instruments with others in the literature, it is concluded that each population require its own algorithm for the presumptive detection of subjects with low bone mass. The algorithm should be reassessed periodically if the characteristics of the population or its social-economic conditions change.]]></description><identifier>ISSN: 0378-5122</identifier><identifier>EISSN: 1873-4111</identifier><identifier>DOI: 10.1016/j.maturitas.2004.08.015</identifier><identifier>PMID: 15978976</identifier><identifier>CODEN: MATUDK</identifier><language>eng</language><publisher>Shannon: Elsevier Ireland Ltd</publisher><subject>Aged ; Biological and medical sciences ; BMD (lumbar vertebrae) ; Body Mass Index ; Bone Density ; Bone Diseases, Metabolic - classification ; Bone Diseases, Metabolic - diagnosis ; Calcium, Dietary - administration & dosage ; Confidence Intervals ; Cross-Sectional Studies ; Diseases of the osteoarticular system ; Female ; Gynecology. Andrology. Obstetrics ; Humans ; Kyphosis - diagnosis ; Kyphosis - diagnostic imaging ; Logistic Models ; Lumbar Vertebrae - physiology ; Medical sciences ; Middle Aged ; Odds Ratio ; Osteoporosis ; Osteoporosis, Postmenopausal - classification ; Osteoporosis, Postmenopausal - diagnosis ; Osteoporosis. Osteomalacia. Paget disease ; Postmenopause ; Puberal and climacteric disorders (male and female) ; Radiography ; Reproducibility of Results ; Risk Factors ; ROC Curve ; Sensitivity and Specificity</subject><ispartof>Maturitas, 2005-07, Vol.51 (3), p.314-324</ispartof><rights>2004 Elsevier Ireland Ltd</rights><rights>2005 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c399t-ff391443f01b4aeca6866a87ccf4172df9fc0a5f4c989e9e58aecdebad98ab643</citedby><cites>FETCH-LOGICAL-c399t-ff391443f01b4aeca6866a87ccf4172df9fc0a5f4c989e9e58aecdebad98ab643</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,777,781,27905,27906</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=16933055$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/15978976$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Masoni, Ana</creatorcontrib><creatorcontrib>Morosano, Mario</creatorcontrib><creatorcontrib>Pezzotto, Stella M.</creatorcontrib><creatorcontrib>Tomat, Florencia</creatorcontrib><creatorcontrib>Bentancur, Fabiana</creatorcontrib><creatorcontrib>Bocanera, Roberto</creatorcontrib><creatorcontrib>Tozzini, Roberto</creatorcontrib><creatorcontrib>Puche, Rodolfo C.</creatorcontrib><title>Construction of two instruments for the presumptive detection of post-menopausal women with low spinal bone mass by means of clinical risk factors</title><title>Maturitas</title><addtitle>Maturitas</addtitle><description><![CDATA[The objective of this investigation was the design of two instruments based on clinical risk factors for the presumptive detection of post-menopausal women with spinal BMD
<
2.5 S.D. below average (LBMD). We investigated the association of 20 risk factors (RF) with LBMD in a series of 131 women. According to current densitometric criteria, subjects were classified as normals (
N
=
33); osteopenics (
N
=
53) and osteoporotics (
N
=
45). Normals and osteopenics were taken as a single group because only ‘nulliparity’ and ‘personal fractures’ exhibited significant differences between these groups. A logistic regression attempting to identify which factors were associated with osteopenia showed a poor fit (pseudo
R
2
=
0.289).
Univariate unconditional logistic regression analysis was used to calculate odd ratios (ORs) and their 95% CI for all RF. Those with associated
P-values <0.100 were included in a multivariate logistic regression analysis to obtain the odds ratios (OR) adjusted by the effects of the others. The variables with not significant
β coefficients were eliminated, producing a reduced model. BMI (<25
kg/m
2), calcium intake (<1.2
g/day), menopause (>10 years), and the simultaneous occurrence of kyphosis and personal fractures showed significant association with low bone mass at the lumbar spine and their effect was additive. Fitting of the data to the model was assessed with the Hosmer–Lemeshow test (
P
=
0.926) The area under the ROC curve is 0.833 (95% CI
=
0.757–0.909). The following equation calculates the probability of having low spinal bone mass:
ln
P
1
−
P
=
−
3.05
+
1.11
(
>
10
years
of
menopause
)
+
1.19
(
Ca
intake
<
1200
mg
/
day
)
+
2.35
(
BMI
<
25
)
−
0.58
(
personal
fractures
)
+
0.38
(
kyphosis
)
+
2.75
(
personal
fractures
+
kyphosis
)
.
The sensitivity, specificity and area under the ROC curve were defined. The point of maximum specificity and sensitivity derived from the ROC curve, has a probability of 0.409. With such a cut-off point, the equation has a sensitivity of 73%, specificity 79%, positive predictive value 65% and negative predictive value 85%.
The second instrument associates very low lumbar bone mass with the number of risk factors accumulated per patient. At baseline, all subjects had four RFs: they were, women, white, post-menopausal, and with no previous exposure to estrogens. With six additional RFs the presumptive diagnosis of LBMD has a specificity of 99%, positive predicting value 94% and false positives 6.5%. The area under the curve in a ROC graph was 0.826 (95% CI
=
0.747–0.914).
Comparing present instruments with others in the literature, it is concluded that each population require its own algorithm for the presumptive detection of subjects with low bone mass. The algorithm should be reassessed periodically if the characteristics of the population or its social-economic conditions change.]]></description><subject>Aged</subject><subject>Biological and medical sciences</subject><subject>BMD (lumbar vertebrae)</subject><subject>Body Mass Index</subject><subject>Bone Density</subject><subject>Bone Diseases, Metabolic - classification</subject><subject>Bone Diseases, Metabolic - diagnosis</subject><subject>Calcium, Dietary - administration & dosage</subject><subject>Confidence Intervals</subject><subject>Cross-Sectional Studies</subject><subject>Diseases of the osteoarticular system</subject><subject>Female</subject><subject>Gynecology. Andrology. Obstetrics</subject><subject>Humans</subject><subject>Kyphosis - diagnosis</subject><subject>Kyphosis - diagnostic imaging</subject><subject>Logistic Models</subject><subject>Lumbar Vertebrae - physiology</subject><subject>Medical sciences</subject><subject>Middle Aged</subject><subject>Odds Ratio</subject><subject>Osteoporosis</subject><subject>Osteoporosis, Postmenopausal - classification</subject><subject>Osteoporosis, Postmenopausal - diagnosis</subject><subject>Osteoporosis. Osteomalacia. Paget disease</subject><subject>Postmenopause</subject><subject>Puberal and climacteric disorders (male and female)</subject><subject>Radiography</subject><subject>Reproducibility of Results</subject><subject>Risk Factors</subject><subject>ROC Curve</subject><subject>Sensitivity and Specificity</subject><issn>0378-5122</issn><issn>1873-4111</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2005</creationdate><recordtype>article</recordtype><recordid>eNqFkcuO1DAQRS0EYpqBXwBvYJdgx3nYy1GLlzQSG1hbjlPWuEns4HKmNb_BF-OmWzNLVqUqn1tl3UvIO85qznj_8VAvJm_JZ4N1w1hbM1kz3j0jOy4HUbWc8-dkx8Qgq443zRV5hXhgjHVMtC_JFe_UINXQ78iffQyY02azj4FGR_MxUv9vtEDISF1MNN8BXRPgtqzZ3wOdIMOjYI2Yq8LG1WxoZnqMpaFHn-_oHI8UVx_KdIwB6GIQ6fhAFzABT1o7--BteU4ef1FnbI4JX5MXzswIby71mvz8_OnH_mt1-_3Lt_3NbWWFUrlyTijetsIxPrYGrOll3xs5WOtaPjSTU84y07nWKqlAQScLNMFoJiXN2Lfimnw4711T_L0BZr14tDDPJkDcUPeDGrquEQUczqBNETGB02vyi0kPmjN9ikMf9GMc-hSHZlKXOIry7eXENi4wPeku_hfg_QUwWHxwyQTr8YnrlRCsOy26OXNQDLn3kDRaD8HC5FOJQk_R__czfwHA07Li</recordid><startdate>20050716</startdate><enddate>20050716</enddate><creator>Masoni, Ana</creator><creator>Morosano, Mario</creator><creator>Pezzotto, Stella M.</creator><creator>Tomat, Florencia</creator><creator>Bentancur, Fabiana</creator><creator>Bocanera, Roberto</creator><creator>Tozzini, Roberto</creator><creator>Puche, Rodolfo C.</creator><general>Elsevier Ireland Ltd</general><general>Elsevier Science</general><scope>IQODW</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope></search><sort><creationdate>20050716</creationdate><title>Construction of two instruments for the presumptive detection of post-menopausal women with low spinal bone mass by means of clinical risk factors</title><author>Masoni, Ana ; Morosano, Mario ; Pezzotto, Stella M. ; Tomat, Florencia ; Bentancur, Fabiana ; Bocanera, Roberto ; Tozzini, Roberto ; Puche, Rodolfo C.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c399t-ff391443f01b4aeca6866a87ccf4172df9fc0a5f4c989e9e58aecdebad98ab643</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2005</creationdate><topic>Aged</topic><topic>Biological and medical sciences</topic><topic>BMD (lumbar vertebrae)</topic><topic>Body Mass Index</topic><topic>Bone Density</topic><topic>Bone Diseases, Metabolic - classification</topic><topic>Bone Diseases, Metabolic - diagnosis</topic><topic>Calcium, Dietary - administration & dosage</topic><topic>Confidence Intervals</topic><topic>Cross-Sectional Studies</topic><topic>Diseases of the osteoarticular system</topic><topic>Female</topic><topic>Gynecology. Andrology. Obstetrics</topic><topic>Humans</topic><topic>Kyphosis - diagnosis</topic><topic>Kyphosis - diagnostic imaging</topic><topic>Logistic Models</topic><topic>Lumbar Vertebrae - physiology</topic><topic>Medical sciences</topic><topic>Middle Aged</topic><topic>Odds Ratio</topic><topic>Osteoporosis</topic><topic>Osteoporosis, Postmenopausal - classification</topic><topic>Osteoporosis, Postmenopausal - diagnosis</topic><topic>Osteoporosis. Osteomalacia. Paget disease</topic><topic>Postmenopause</topic><topic>Puberal and climacteric disorders (male and female)</topic><topic>Radiography</topic><topic>Reproducibility of Results</topic><topic>Risk Factors</topic><topic>ROC Curve</topic><topic>Sensitivity and Specificity</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Masoni, Ana</creatorcontrib><creatorcontrib>Morosano, Mario</creatorcontrib><creatorcontrib>Pezzotto, Stella M.</creatorcontrib><creatorcontrib>Tomat, Florencia</creatorcontrib><creatorcontrib>Bentancur, Fabiana</creatorcontrib><creatorcontrib>Bocanera, Roberto</creatorcontrib><creatorcontrib>Tozzini, Roberto</creatorcontrib><creatorcontrib>Puche, Rodolfo C.</creatorcontrib><collection>Pascal-Francis</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Maturitas</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Masoni, Ana</au><au>Morosano, Mario</au><au>Pezzotto, Stella M.</au><au>Tomat, Florencia</au><au>Bentancur, Fabiana</au><au>Bocanera, Roberto</au><au>Tozzini, Roberto</au><au>Puche, Rodolfo C.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Construction of two instruments for the presumptive detection of post-menopausal women with low spinal bone mass by means of clinical risk factors</atitle><jtitle>Maturitas</jtitle><addtitle>Maturitas</addtitle><date>2005-07-16</date><risdate>2005</risdate><volume>51</volume><issue>3</issue><spage>314</spage><epage>324</epage><pages>314-324</pages><issn>0378-5122</issn><eissn>1873-4111</eissn><coden>MATUDK</coden><abstract><![CDATA[The objective of this investigation was the design of two instruments based on clinical risk factors for the presumptive detection of post-menopausal women with spinal BMD
<
2.5 S.D. below average (LBMD). We investigated the association of 20 risk factors (RF) with LBMD in a series of 131 women. According to current densitometric criteria, subjects were classified as normals (
N
=
33); osteopenics (
N
=
53) and osteoporotics (
N
=
45). Normals and osteopenics were taken as a single group because only ‘nulliparity’ and ‘personal fractures’ exhibited significant differences between these groups. A logistic regression attempting to identify which factors were associated with osteopenia showed a poor fit (pseudo
R
2
=
0.289).
Univariate unconditional logistic regression analysis was used to calculate odd ratios (ORs) and their 95% CI for all RF. Those with associated
P-values <0.100 were included in a multivariate logistic regression analysis to obtain the odds ratios (OR) adjusted by the effects of the others. The variables with not significant
β coefficients were eliminated, producing a reduced model. BMI (<25
kg/m
2), calcium intake (<1.2
g/day), menopause (>10 years), and the simultaneous occurrence of kyphosis and personal fractures showed significant association with low bone mass at the lumbar spine and their effect was additive. Fitting of the data to the model was assessed with the Hosmer–Lemeshow test (
P
=
0.926) The area under the ROC curve is 0.833 (95% CI
=
0.757–0.909). The following equation calculates the probability of having low spinal bone mass:
ln
P
1
−
P
=
−
3.05
+
1.11
(
>
10
years
of
menopause
)
+
1.19
(
Ca
intake
<
1200
mg
/
day
)
+
2.35
(
BMI
<
25
)
−
0.58
(
personal
fractures
)
+
0.38
(
kyphosis
)
+
2.75
(
personal
fractures
+
kyphosis
)
.
The sensitivity, specificity and area under the ROC curve were defined. The point of maximum specificity and sensitivity derived from the ROC curve, has a probability of 0.409. With such a cut-off point, the equation has a sensitivity of 73%, specificity 79%, positive predictive value 65% and negative predictive value 85%.
The second instrument associates very low lumbar bone mass with the number of risk factors accumulated per patient. At baseline, all subjects had four RFs: they were, women, white, post-menopausal, and with no previous exposure to estrogens. With six additional RFs the presumptive diagnosis of LBMD has a specificity of 99%, positive predicting value 94% and false positives 6.5%. The area under the curve in a ROC graph was 0.826 (95% CI
=
0.747–0.914).
Comparing present instruments with others in the literature, it is concluded that each population require its own algorithm for the presumptive detection of subjects with low bone mass. The algorithm should be reassessed periodically if the characteristics of the population or its social-economic conditions change.]]></abstract><cop>Shannon</cop><pub>Elsevier Ireland Ltd</pub><pmid>15978976</pmid><doi>10.1016/j.maturitas.2004.08.015</doi><tpages>11</tpages></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0378-5122 |
| ispartof | Maturitas, 2005-07, Vol.51 (3), p.314-324 |
| issn | 0378-5122 1873-4111 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_67975523 |
| source | Elsevier |
| subjects | Aged Biological and medical sciences BMD (lumbar vertebrae) Body Mass Index Bone Density Bone Diseases, Metabolic - classification Bone Diseases, Metabolic - diagnosis Calcium, Dietary - administration & dosage Confidence Intervals Cross-Sectional Studies Diseases of the osteoarticular system Female Gynecology. Andrology. Obstetrics Humans Kyphosis - diagnosis Kyphosis - diagnostic imaging Logistic Models Lumbar Vertebrae - physiology Medical sciences Middle Aged Odds Ratio Osteoporosis Osteoporosis, Postmenopausal - classification Osteoporosis, Postmenopausal - diagnosis Osteoporosis. Osteomalacia. Paget disease Postmenopause Puberal and climacteric disorders (male and female) Radiography Reproducibility of Results Risk Factors ROC Curve Sensitivity and Specificity |
| title | Construction of two instruments for the presumptive detection of post-menopausal women with low spinal bone mass by means of clinical risk factors |
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