scholarly journals Bone Loss Rate May Interact with Other Risk Factors for Fractures among Elderly Women: A 15-Year Population-Based Study

2010 ◽  
Vol 2010 ◽  
pp. 1-10 ◽  
Author(s):  
Joonas Sirola ◽  
Anna-Kaisa Koistinen ◽  
Kari Salovaara ◽  
Toni Rikkonen ◽  
Marjo Tuppurainen ◽  
...  

Aim was to investigate fracture risk (FR) according to bone loss (BL) rate. A random sample of 1652 women aged 53.5 years was measured with dual X-ray absorptiometry in femoral neck in 1989 and 1994 and divided into tertiles of annual BL rate: high >0.84%, moderate 0.13%–0.84%, and low <0.13%. Low trauma energy fractures during following 10 years were recorded. There were no differences in FR between BL tertiles in Cox regression model. Factors predicting lower FR in Cox model were in high tertile: high T-score (HR 0.71; 95% CI 0.54–0.93,P=.012), no sister's fracture (HR 0.35; 0.19–0.64,P=.001), no mother's fracture (HR 0.52; 0.31–0.88,P=.015), in moderate tertile: high T-score (HR 0.69;0.53–0.91,P=.008) and good grip strength (HR 0.98; 0.97–0.99,P=.022). In low tertile there were no predictors for FR. BL predicted FR in women with mother's fracture in univariate and multivariate model (OR 2.6; 1.15–5.7,P=.021) but with sister's fracture this was observed only in multivariate model (OR 2.66; 1.09–6.7,P=.039). Accordingly, the risk factors for postmenopausal fractures, especially mother's fracture, may interact with BL.

Bone ◽  
2006 ◽  
Vol 39 (2) ◽  
pp. 385-391 ◽  
Author(s):  
R. Korpelainen ◽  
J. Korpelainen ◽  
J. Heikkinen ◽  
K. Väänänen ◽  
S. Keinänen-Kiukaanniemi

2008 ◽  
Vol 19 (8) ◽  
pp. 1211-1217 ◽  
Author(s):  
G. Zhai ◽  
D. J. Hart ◽  
A. M. Valdes ◽  
B. S. Kato ◽  
J. B. Richards ◽  
...  

Diseases ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 43
Author(s):  
Ana M. Della Rocca ◽  
Fernanda S. Tonin ◽  
Mariana M. Fachi ◽  
Alexandre F. Cobre ◽  
Vinicius L. Ferreira ◽  
...  

Burkitt lymphoma/leukemia (BL/L) is an aggressive oncohematological disease. This study evaluated the population-based prognosis and survival on BL/L as well as if BL/L behaved as a risk factor for the development of second primary cancers (SPCs) and if other first tumors behaved as risk factors for the occurrence of BL/L as an SPC. A retrospective cohort using the Surveillance, Epidemiology and End Results (SEER) Program (2008–2016) was performed. Kaplan–Meier, time-dependent covariate Cox regression and Poisson regression models were conducted. Overall, 3094 patients were included (median, 45 years; IQR, 22–62). The estimated overall survival was 65.4 months (95% CI, 63.6–67.3). Significantly more deaths occurred for older patients, black race, disease at an advanced stage, patients without chemotherapy/surgery and patients who underwent radiotherapy. Hodgkin lymphomas (nodal) (RR, 7.6 (3.9–15.0; p < 0.001)), Kaposi sarcomas (34.0 (16.8–68.9; p < 0.001)), liver tumors (3.4 (1.2–9.3; p = 0.020)) and trachea, mediastinum and other respiratory cancers (15.8 (2.2–113.9; p = 0.006)) behaved as risk factors for the occurrence of BL/L as an SPC. BL/L was a risk factor for the occurrence of SPCs as acute myeloid leukemias (4.6 (2.1–10.4; p < 0.001)), Hodgkin lymphomas (extranodal) (74.3 (10.0–549.8; p < 0.001)) and Kaposi sarcomas (35.1 (12.1–101.4; p < 0.001)). These results may assist the development of diagnostic and clinical recommendations for BL/L.


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