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Thach Tran - One of the best experts on this subject based on the ideXlab platform.
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a risk assessment tool for predicting fragility fractures and mortality in the elderly
Journal of Bone and Mineral Research, 2020Co-Authors: Jonathan D Adachi, Claudie Berger, Thach Tran, Dana Bliuc, Hanh M Pham, Tineke A C M Van Geel, Joop P W Van Den Bergh, John A EismanAbstract:Existing fracture risk assessment tools are not designed to predict fracture-associated consequences, possibly contributing to the current undermanagement of fragility fractures worldwide. We aimed to develop a risk assessment tool for predicting the conceptual risk of fragility fractures and its consequences. The study involved 8965 people aged ≥60 years from the Dubbo Osteoporosis Epidemiology Study and the Canadian Multicentre Osteoporosis Study. Incident fracture was identified from X-ray reports and questionnaires, and death was ascertained though contact with a family member or obituary review. We used a Multistate Model to quantify the effects of the predictors on the transition risks to an initial and subsequent incident fracture and mortality, accounting for their complex interrelationships, confounding effects, and death as a competing risk. There were 2364 initial fractures, 755 subsequent fractures, and 3300 deaths during a median follow-up of 13 years (interquartile range [IQR] 7-15). The prediction Model included sex, age, bone mineral density, history of falls within 12 previous months, prior fracture after the age of 50 years, cardiovascular diseases, diabetes mellitus, chronic pulmonary diseases, hypertension, and cancer. The Model accurately predicted fragility fractures up to 11 years of follow-up and post-fracture mortality up to 9 years, ranging from 7 years after hip fractures to 15 years after non-hip fractures. For example, a 70-year-old woman with a T-score of -1.5 and without other risk factors would have 10% chance of sustaining a fracture and an 8% risk of dying in 5 years. However, after an initial fracture, her risk of sustaining another fracture or dying doubles to 33%, ranging from 26% after a distal to 42% post hip fracture. A robust statistical technique was used to develop a prediction Model for individualization of progression to fracture and its consequences, facilitating informed decision making about risk and thus treatment for individuals with different risk profiles. © 2020 American Society for Bone and Mineral Research.
Neda Stjepanovic - One of the best experts on this subject based on the ideXlab platform.
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association of premenopausal risk reducing salpingo oophorectomy with breast cancer risk in brca1 2 mutation carriers maximising bias reduction
European Journal of Cancer, 2020Co-Authors: Neda Stjepanovic, Guillermo Villacampa, Kevin T Nead, Sara Torresesquius, Guadalupe Gomez Melis, Katherine L Nathanson, A Teule, Joan BrunetAbstract:Abstract Background Whether risk-reducing salpingo-oophorectomy (RRSO) in BRCA1/2 carriers reduces the breast cancer (BC) risk is conflicting, potentially due to methodological issues of prior analysis. We analysed the association between premenopausal RRSO and BC risk in BRCA1/2 carriers after adjusting for potential biases. Methods We analysed data from 444 BRCA1 and 409 BRCA2 carriers under age 51 with no cancer prior to genetic testing or during first 6 months of surveillance (to avoid cancer-induced testing bias and prevalent-cancer bias). Observation started 6 months after genetic testing (to avoid event-free time bias), until BC diagnosis, risk-reducing mastectomy (RRM) or death. A Multistate Model with four states (non-RRSO, RRSO, RRM and BC) and five transitions was fitted to characterise outcomes and to calculate the BC risk reduction after premenopausal RRSO (before age 51). A systematic review was performed to assess the association between premenopausal RRSO and BC. Results During a mean follow-up of 4.3 years, 96 women (11.3%) developed BC (54 BRCA1, 42 BRCA2). The risk of BC after premenopausal RRSO decreased significantly in BRCA1 carriers (hazard ratio (HR) = 0.45 [95% confidence interval (CI):0.22–0.92]), but was not conclusive in BRCA2 carriers (HR = 0.77 [95%CI:0.35–1.67]). The systematic review suggested that premenopausal RRSO is associated with a decrease of BC risk in both BRCA1 and BRCA2 carriers. Conclusions Premenopausal RRSO was associated with BC risk reduction in BRCA1 carriers, which can help guide cancer risk-reducing strategies in this population. Longer follow-up and larger sample size may be needed to estimate the potential benefit in BRCA2 carriers.
John A Eisman - One of the best experts on this subject based on the ideXlab platform.
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a risk assessment tool for predicting fragility fractures and mortality in the elderly
Journal of Bone and Mineral Research, 2020Co-Authors: Jonathan D Adachi, Claudie Berger, Thach Tran, Dana Bliuc, Hanh M Pham, Tineke A C M Van Geel, Joop P W Van Den Bergh, John A EismanAbstract:Existing fracture risk assessment tools are not designed to predict fracture-associated consequences, possibly contributing to the current undermanagement of fragility fractures worldwide. We aimed to develop a risk assessment tool for predicting the conceptual risk of fragility fractures and its consequences. The study involved 8965 people aged ≥60 years from the Dubbo Osteoporosis Epidemiology Study and the Canadian Multicentre Osteoporosis Study. Incident fracture was identified from X-ray reports and questionnaires, and death was ascertained though contact with a family member or obituary review. We used a Multistate Model to quantify the effects of the predictors on the transition risks to an initial and subsequent incident fracture and mortality, accounting for their complex interrelationships, confounding effects, and death as a competing risk. There were 2364 initial fractures, 755 subsequent fractures, and 3300 deaths during a median follow-up of 13 years (interquartile range [IQR] 7-15). The prediction Model included sex, age, bone mineral density, history of falls within 12 previous months, prior fracture after the age of 50 years, cardiovascular diseases, diabetes mellitus, chronic pulmonary diseases, hypertension, and cancer. The Model accurately predicted fragility fractures up to 11 years of follow-up and post-fracture mortality up to 9 years, ranging from 7 years after hip fractures to 15 years after non-hip fractures. For example, a 70-year-old woman with a T-score of -1.5 and without other risk factors would have 10% chance of sustaining a fracture and an 8% risk of dying in 5 years. However, after an initial fracture, her risk of sustaining another fracture or dying doubles to 33%, ranging from 26% after a distal to 42% post hip fracture. A robust statistical technique was used to develop a prediction Model for individualization of progression to fracture and its consequences, facilitating informed decision making about risk and thus treatment for individuals with different risk profiles. © 2020 American Society for Bone and Mineral Research.
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A risk assessment tool for predicting fragility fractures and mortality in the elderly.
'Wiley', 2020Co-Authors: Tran T, John A Eisman, Bliuc D, Hm Pham, Van Geel T, Jd Adachi, Berger C, Van Den Bergh J, Geusens P, Goltzman DAbstract:Existing fracture risk assessment tools are not designed to predict fracture-associated consequences, possibly contributing to the current under-management of fragility fractures worldwide. We aimed to develop a risk assessment tool for predicting the conceptual risk of fragility fractures and consequences. The study involved 8965 people aged ≥60 years from the Dubbo Osteoporosis Epidemiology Study and the Canadian Multicentre Osteoporosis Study. Incident fracture was identified from X-ray reports and questionnaires, and death ascertained though contact with a family member or obituary review. We used Multistate Model to quantify the effects of the predictors on the transition risks to an initial and subsequent incident fracture, and mortality, accounting for their complex inter-relationships, confounding effects and death as a competing risk. There were 2364 initial fractures, 755 subsequent fractures, and 3300 deaths during a median follow up of 13 years (IQR: 7, 15). The prediction Model included gender, age, BMD, history of falls within 12 previous months, prior fracture after the age of 50 years, cardiovascular diseases, diabetes mellitus, chronic pulmonary diseases, hypertension and cancer. The Model accurately predicted fragility fractures up to 11 years of follow up, and post-fracture mortality up to 9 years, ranging from 7 years following hip fractures to 15 years following non-hip fractures. For example, a 70-year old woman with a T-score of -1.5 and without other risk factors would have 10% chance of sustaining a fracture and an 8% risk of dying in 5 years. However, after an initial fracture, her risk of sustaining another fracture or dying doubles to 33%, ranging from 26% following a distal to 42% post hip fracture. A robust statistical technique was used to develop a prediction Model for individualisation of progression to fracture and its consequences, facilitating informed decision making about risk and thus treatment for individuals with different risk profiles. This article is protected by copyright. All rights reserved
Paul C Lambert - One of the best experts on this subject based on the ideXlab platform.
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A Multistate Model incorporating estimation of excess hazards and multiple time scales
2021Co-Authors: Caroline E Weibull, Paul C Lambert, Sandra Eloranta, Therese Ml Andersson, Paul W Dickman, Michael J CrowtherAbstract:As cancer patient survival improves, late effects from treatment are becoming the next clinical challenge. Chemotherapy and radiotherapy, for example, potentially increase the risk of both morbidity and mortality from second malignancies and cardiovascular disease. To provide clinically relevant population-level measures of late effects, it is of importance to (1) simultaneously estimate the risks of both morbidity and mortality, (2) partition these risks into the component expected in the absence of cancer and the component due to the cancer and its treatment, and (3) incorporate the multiple time scales of attained age, calendar time, and time since diagnosis. Multistate Models provide a framework for simultaneously studying morbidity and mortality, but do not solve the problem of partitioning the risks. However, this partitioning can be achieved by applying a relative survival framework, allowing us to directly quantify the excess risk. This article proposes a combination of these two frameworks, providing one approach to address (1) to (3). Using recently developed methods in Multistate Modeling, we incorporate estimation of excess hazards into a Multistate Model. Both intermediate and absorbing state risks can be partitioned and different transitions are allowed to have different and/or multiple time scales. We illustrate our approach using data on Hodgkin lymphoma patients and excess risk of diseases of the circulatory system, and provide user-friendly Stata software with accompanying example code
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parametric Multistate survival Models flexible Modelling allowing transition specific distributions with application to estimating clinically useful measures of effect differences
Statistics in Medicine, 2017Co-Authors: Paul C Lambert, Michael J CrowtherAbstract:Multistate Models are increasingly being used to Model complex disease profiles. By Modelling transitions between disease states, accounting for competing events at each transition, we can gain a much richer understanding of patient trajectories and how risk factors impact over the entire disease pathway. In this article, we concentrate on parametric Multistate Models, both Markov and semi-Markov, and develop a flexible framework where each transition can be specified by a variety of parametric Models including exponential, Weibull, Gompertz, Royston-Parmar proportional hazards Models or log-logistic, log-normal, generalised gamma accelerated failure time Models, possibly sharing parameters across transitions. We also extend the framework to allow time-dependent effects. We then use an efficient and generalisable simulation method to calculate transition probabilities from any fitted Multistate Model, and show how it facilitates the simple calculation of clinically useful measures, such as expected length of stay in each state, and differences and ratios of proportion within each state as a function of time, for specific covariate patterns. We illustrate our methods using a dataset of patients with primary breast cancer. User-friendly Stata software is provided.
Joan Brunet - One of the best experts on this subject based on the ideXlab platform.
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association of premenopausal risk reducing salpingo oophorectomy with breast cancer risk in brca1 2 mutation carriers maximising bias reduction
European Journal of Cancer, 2020Co-Authors: Neda Stjepanovic, Guillermo Villacampa, Kevin T Nead, Sara Torresesquius, Guadalupe Gomez Melis, Katherine L Nathanson, A Teule, Joan BrunetAbstract:Abstract Background Whether risk-reducing salpingo-oophorectomy (RRSO) in BRCA1/2 carriers reduces the breast cancer (BC) risk is conflicting, potentially due to methodological issues of prior analysis. We analysed the association between premenopausal RRSO and BC risk in BRCA1/2 carriers after adjusting for potential biases. Methods We analysed data from 444 BRCA1 and 409 BRCA2 carriers under age 51 with no cancer prior to genetic testing or during first 6 months of surveillance (to avoid cancer-induced testing bias and prevalent-cancer bias). Observation started 6 months after genetic testing (to avoid event-free time bias), until BC diagnosis, risk-reducing mastectomy (RRM) or death. A Multistate Model with four states (non-RRSO, RRSO, RRM and BC) and five transitions was fitted to characterise outcomes and to calculate the BC risk reduction after premenopausal RRSO (before age 51). A systematic review was performed to assess the association between premenopausal RRSO and BC. Results During a mean follow-up of 4.3 years, 96 women (11.3%) developed BC (54 BRCA1, 42 BRCA2). The risk of BC after premenopausal RRSO decreased significantly in BRCA1 carriers (hazard ratio (HR) = 0.45 [95% confidence interval (CI):0.22–0.92]), but was not conclusive in BRCA2 carriers (HR = 0.77 [95%CI:0.35–1.67]). The systematic review suggested that premenopausal RRSO is associated with a decrease of BC risk in both BRCA1 and BRCA2 carriers. Conclusions Premenopausal RRSO was associated with BC risk reduction in BRCA1 carriers, which can help guide cancer risk-reducing strategies in this population. Longer follow-up and larger sample size may be needed to estimate the potential benefit in BRCA2 carriers.
