Abstract:A mapping algorithm was developed for mapping of AcroQoL to EQ-5D, using patient level data from three previously published studies, and including validation in the confirmatory sub-sample. Mean (SD) utilities index in this study population was estimated as 0.71 (0.28). Additional research may be needed to test this mapping algorithm in other acromegaly populations.
“…In the AcroQoL (n =74), all the scores, including the total, physical, and psychological, were low (63.4 ± 19.8%, 61.1 ± 23.9%, and 64.8 ± 19.1%, respectively) (Table 2), as in previous report (23). In the SF-36 (n =61), the PCS score was negatively associated with age (adjusted R 2 =0.24, P <0.01), while both MCS and RCS scores were positively associated with age (adjusted R 2 = 0.13, P <0.01, adjusted R 2 =0.05, P =0.03, respectively) (Figures 1A-C).…”
Section: Association Between Age and Qolsupporting
ContextWith the increasing number of older patients with acromegaly, it is important to understand the effects of aging on the quality of life (QoL) in acromegaly.ObjectiveTo investigate the factors associated with the QoL of older acromegaly patients.DesignThis was a single-center, retrospective, cross-sectional study conducted between 2014 and 2019.MethodsAmong 90 acromegaly patients at Kobe University Hospital, 74 who had completed the QoL evaluation under treatment were enrolled (age = 62.0 [50.7–70.0], female 52%). SF-36 and the AcroQoL questionnaire were used to quantify QoL. The patients were divided into two groups: the young and middle-aged group, aged <65 years (51.0 [46.0–59.2], n =42), and the older group, aged ≥65 years (70.5 [69.0–73.0], n =32). The factors associated with the QoL scores were analyzed using univariate and multivariate regression analyses.ResultsThe scores for the physical component summary of SF-36 were negatively associated with age (P <0.01), while those for the mental or role/social component summary were positively associated (P <0.01, P =0.03, respectively). In contrast, AcroQoL scores were not associated with age. However, the different factors were associated with lower AcroQoL scores; arthropathy and higher BMI in the older group (P <0.01, and P =0.01, respectively), and treatment modalities and size of pituitary tumor in the young and middle-aged group (P <0.01, P =0.04, respectively). Replacement of hydrocortisone was commonly associated both in young and middle-aged group (P =0.04), and in older group (P =0.02).ConclusionWe showed that the factors associated with impaired QoL differed in the young and middle-aged, and older patients with acromegaly. In older patients, arthropathy and higher BMI were associated with poor QoL. These suggest the importance of early diagnosis and appropriate treatment in preventing arthropathy in acromegaly.
“…In the AcroQoL (n =74), all the scores, including the total, physical, and psychological, were low (63.4 ± 19.8%, 61.1 ± 23.9%, and 64.8 ± 19.1%, respectively) (Table 2), as in previous report (23). In the SF-36 (n =61), the PCS score was negatively associated with age (adjusted R 2 =0.24, P <0.01), while both MCS and RCS scores were positively associated with age (adjusted R 2 = 0.13, P <0.01, adjusted R 2 =0.05, P =0.03, respectively) (Figures 1A-C).…”
Section: Association Between Age and Qolsupporting
ContextWith the increasing number of older patients with acromegaly, it is important to understand the effects of aging on the quality of life (QoL) in acromegaly.ObjectiveTo investigate the factors associated with the QoL of older acromegaly patients.DesignThis was a single-center, retrospective, cross-sectional study conducted between 2014 and 2019.MethodsAmong 90 acromegaly patients at Kobe University Hospital, 74 who had completed the QoL evaluation under treatment were enrolled (age = 62.0 [50.7–70.0], female 52%). SF-36 and the AcroQoL questionnaire were used to quantify QoL. The patients were divided into two groups: the young and middle-aged group, aged <65 years (51.0 [46.0–59.2], n =42), and the older group, aged ≥65 years (70.5 [69.0–73.0], n =32). The factors associated with the QoL scores were analyzed using univariate and multivariate regression analyses.ResultsThe scores for the physical component summary of SF-36 were negatively associated with age (P <0.01), while those for the mental or role/social component summary were positively associated (P <0.01, P =0.03, respectively). In contrast, AcroQoL scores were not associated with age. However, the different factors were associated with lower AcroQoL scores; arthropathy and higher BMI in the older group (P <0.01, and P =0.01, respectively), and treatment modalities and size of pituitary tumor in the young and middle-aged group (P <0.01, P =0.04, respectively). Replacement of hydrocortisone was commonly associated both in young and middle-aged group (P =0.04), and in older group (P =0.02).ConclusionWe showed that the factors associated with impaired QoL differed in the young and middle-aged, and older patients with acromegaly. In older patients, arthropathy and higher BMI were associated with poor QoL. These suggest the importance of early diagnosis and appropriate treatment in preventing arthropathy in acromegaly.
“…Besides the SF-36, other brief generic questionnaires such as the EuroQoL-5D [ 38 ] have been used in pituitary patients [ 39 – 41 ]. However, this widely used questionnaire only consists of five items, limiting its ability to provide a comprehensive view on the self-perceived health of patients with complex conditions such as pituitary diseases.…”
Purpose
Pituitary diseases severely affect patients’ health-related quality of life (HRQoL). The most frequently used generic HRQoL questionnaire is the Short Form-36 (SF-36). The shorter 12-item version (SF-12) can improve efficiency of patient monitoring. This study aimed to determine whether SF-12 can replace SF-36 in pituitary care.
Methods
In a longitudinal cohort study (August 2016 to December 2018) among 103 endoscopically operated adult pituitary tumor patients, physical and mental component scores (PCS and MCS) of SF-36 and SF-12 were measured preoperatively, and 6 weeks and 6 months postoperatively. Chronic care was assessed with a cross-sectional study (N = 431). Mean differences and agreement between SF-36 and SF-12 change in scores (preoperative vs. 6 months) were assessed with intraclass correlation coefficients (ICC) and limits of agreement, depicting 95% of individual patients.
Results
In the longitudinal study, mean differences between change in SF-36 and SF-12 scores were 1.4 (PCS) and 0.4 (MCS) with fair agreement for PCS (ICC = 0.546) and substantial agreement for MCS (ICC = 0.931). For 95% of individual patients, the difference between change in SF-36 and SF-12 scores varied between −14.0 and 16.9 for PCS and between −7.8 and 8.7 for MCS. Cross-sectional results showed fair agreement for PCS (ICC = 0.597) and substantial agreement for MCS (ICC = 0.943).
Conclusions
On a group level, SF-12 can reliably reproduce MCS in pituitary patients, although PCS is less well correlated. However, individual differences between SF-36 and SF-12 can be large. For pituitary diseases, alternative strategies are needed for concise, but comprehensive patient-reported outcome measurement.
“…The AcroQoL is also often used to validate other questionnaires on well-being and quality of life used in the general population and acromegaly-specific tools, such as the acromegaly treatment satisfaction questionnaire (Acro-TSQ) [ 14 ] and SAGIT ® [ 5 ]. It was also used in comparison with EuroQoL instrument (EQ-5D-5L), Short Form-12 (SF12), Short Form-36 (SF36), EQ-5D-3L and sociodemographic questionnaire to determine a grade of comparison between different tools [ 5 , 9 , 14 , 16 , 17 , 20 ]. Despite the increasing use of the AcroQoL and its recognition as a useful clinical tool, the investigation of the relationship between biochemical disease control and quality of life is still considered a controversial topic, because of the inconclusive consistency of evidence across different studies [ 56 , 57 ].…”
Purpose
Acromegaly is a rare chronic disease characterized by systemic comorbidity and reduced quality of life. Although achieving biochemical control has always been the primary goal of acromegaly therapy, recent evidence has shown that the traditional assessment does not adequately capture the complexity of symptoms and patients’ perception. These findings result in the need to improve a fast decision-making process of the clinician, who should not only take into account biochemical–instrumental criteria, but also patients’ symptoms. With the aim of supporting the clinician in the diagnostic and therapeutic decision-making process several disease-specific tools have been developed. The aim of this review is to provide a description of the acromegaly-specific tools, presenting their main features, their application in daily practice, and their efficacy and utility.
Methods
A systematic search of Medline/PubMed, ISI-Web of Knowledge, and Google Scholar databases was done.
Results
Specific instruments and questionnaires have recently been developed to assist clinicians in the assessment of acromegaly. These are either Patient-Reported Outcome tools, such as Acromegaly Quality of Life Questionnaire (AcroQoL) and Pain Assessment Acromegaly Symptom Questionnaire (PASQ), or Clinician-Reported Outcome tools, such as ACROSCORE, SAGIT® and Acromegaly Disease Activity Tool (ACRODAT®). Such tools are extremely flexible and, therefore, have been widely adopted by endocrinologists and other professionals, so much so that they have also been included as recommendations in the 2018 international guidelines.
Conclusion
Questionnaires and tools are useful in the management of acromegaly patients. They help clinicians evaluate patients’ symptoms and could assist in the evaluation of disease activity.
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