OBJECTIVE: Even if treated, acromegaly has a considerable impact on patient quality of life (QoL); despite this, the exact clinical determinants of QoL in acromegaly are unknown. This study retrospectively examines a cohort of treated patients with acromegaly, with the aim of identifying these determinants. METHODS: Retrospective survey analysis, with 165 patients included in the study. All patients completed a survey, which included demographic data and the clinical details of their disease, the Short Form-36 Health Survey (SF-36), the revised Beck Depression Inventory (BDI-II), and the Bern Embitterment Inventory (BEI). Stepwise regression was used to identify predictors of QoL. RESULTS: The strongest predictors of the physical component score of the SF-36 were (in order of declining strength of association): Delay between first presentation of the disease and diagnosis, body mass index (BMI), number of doctors visited before the diagnosis of acromegaly, and age at diagnosis. For the mental component score, the strongest predictors were: number of doctors visited, previous radiotherapy, and age at study entry; and, for the BDI-II score: number of doctors visited, previous radiotherapy, age at study entry, and employment status at the time of diagnosis. The following were predictors of the BEI score: number of doctors visited, and age at study entry. CONCLUSION: Diagnostic delay and lack of diagnostic acumen in medical care provision are strong predictors of poor QoL in patients with acromegaly. Other identified parameters are radiotherapy, age, BMI, and employment status. An efficient acromegaly service should address these aspects when devising disease management plans. ABBREVIATIONS: BDI-II = Beck Depression Inventory II BEI = Bern Embitterment Inventory BMI = body mass index IGF-1 = insulin-like growth factor 1 MCS = mental component summary (score) PCS = physical component summary (score) QoL = quality of life SDS = standard deviation score SF-36 = Short Form-36 Health Survey.
OBJECTIVE: Even if treated, acromegaly has a considerable impact on patient quality of life (QoL); despite this, the exact clinical determinants of QoL in acromegaly are unknown. This study retrospectively examines a cohort of treated patients with acromegaly, with the aim of identifying these determinants. METHODS: Retrospective survey analysis, with 165 patients included in the study. All patients completed a survey, which included demographic data and the clinical details of their disease, the Short Form-36 Health Survey (SF-36), the revised Beck Depression Inventory (BDI-II), and the Bern Embitterment Inventory (BEI). Stepwise regression was used to identify predictors of QoL. RESULTS: The strongest predictors of the physical component score of the SF-36 were (in order of declining strength of association): Delay between first presentation of the disease and diagnosis, body mass index (BMI), number of doctors visited before the diagnosis of acromegaly, and age at diagnosis. For the mental component score, the strongest predictors were: number of doctors visited, previous radiotherapy, and age at study entry; and, for the BDI-II score: number of doctors visited, previous radiotherapy, age at study entry, and employment status at the time of diagnosis. The following were predictors of the BEI score: number of doctors visited, and age at study entry. CONCLUSION: Diagnostic delay and lack of diagnostic acumen in medical care provision are strong predictors of poor QoL in patients with acromegaly. Other identified parameters are radiotherapy, age, BMI, and employment status. An efficient acromegaly service should address these aspects when devising disease management plans. ABBREVIATIONS: BDI-II = Beck Depression Inventory II BEI = Bern Embitterment Inventory BMI = body mass index IGF-1 = insulin-like growth factor 1 MCS = mental component summary (score) PCS = physical component summary (score) QoL = quality of life SDS = standard deviation score SF-36 = Short Form-36 Health Survey.
Authors: Maria Fleseriu; Beverly M K Biller; Pamela U Freda; Monica R Gadelha; Andrea Giustina; Laurence Katznelson; Mark E Molitch; Susan L Samson; Christian J Strasburger; A J van der Lely; Shlomo Melmed Journal: Pituitary Date: 2020-10-20 Impact factor: 4.107
Authors: Maria Fleseriu; Leon Fogelfeld; Murray B Gordon; Jill Sisco; Hilary H Colwell; William H Ludlam; Asi Haviv; Susan D Mathias Journal: Pituitary Date: 2019-12 Impact factor: 4.107