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      Quality of Life (QoL) assessment in a cohort of patients with Phenylketonuria

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          Phenylketonuria (PKU) is a chronic inborn error of amino acid metabolism that requires lifelong follow-up and intervention, which may represent strains on Quality of Life (QoL). This observational study evaluated QoL in a cohort of PKU patients, using updated and detailed instruments.


          22 patients with mild PKU respondent to BH 4 and 21 patients with classical PKU treated with diet were recruited in this study. Adult patients completed WHOQOL questionnaire-100 (WHOQOL-100) and pediatric patients the Pediatric QoL inventory (PedsQL TM). Psychiatric and mood disorders were also evaluated using TAD or BDI and STAI-Y inventories. A multivariable linear regression model was fitted to investigate the predictors of QoL, including age, sex, treatment type, length of current treatment, educational level and employment status (only for adults) as covariates. Results were presented as regression coefficients with 95% confidence interval.


          Global QoL scores were within normal range both in patients with mild and classical disease but global QoL scores were significantly higher in patients with mild PKU under BH 4 treatment as compared to those affected by classical disease who were under diet regimen. Furthermore, QoL significantly increased in long treated PKU patients. Among adult patients, QoL scores were significantly lower in males, in patients with lower education and in those employed or unemployed as compared to students (baseline).


          Both diet and medical treatment based upon BH 4 seem to be associated with higher QoL in the long run. However, patients with mild PKU can rely on BH 4 to achieve a higher Phe tolerance and a better compliance to therapy due to diet relaxation/avoidance. Some specific categories of patients with a lower QoL should be investigated more in depth, engaging with those at risk of lower treatment compliance. The questionnaires employed in the present study seemed to be able to effectively detect criticalities in QoL assessment and represent an advance from previous inventories employed in the past.

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          Most cited references 42

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          The World Health Organization Quality of Life Assessment (WHOQOL): development and general psychometric properties.

           M Power,  B Murphy,  W Kuyken (1998)
          This paper reports on the field testing, empirical derivation and psychometric properties of the World Health Organisation Quality of Life assessment (the WHOQOL). The steps are presented from the development of the initial pilot version of the instrument to the field trial version, the so-called WHOQOL-100. The instrument has been developed collaboratively in a number of centres in diverse cultural settings over several years; data are presented on the performance of the instrument in 15 different settings worldwide.
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            How practical are recommendations for dietary control in phenylketonuria?

            In patients with phenylketonuria, blood phenylalanine concentration during childhood is the major determinant of cognitive outcome. Guidelines provide age-related recommendations for treatment. To ascertain the extent to which these aims are achievable, we audited results from four centres for the years 1994-2000. The median proportion of samples with phenylalanine concentrations above those recommended was less than 30% for those younger than age 10 years but almost 80% for those aged 15 years and older. Similarly, the median frequency of blood sampling, expressed as a proportion of that recommended, was more than 80% for patients younger than 10 years but less than 50% by age 15 years. Our results indicate the difficulty of maintaining control in phenylketonuria, especially in older rather than younger children.
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              Do the SF-36 and WHOQOL-BREF measure the same constructs? Evidence from the Taiwan population*.

              The SF-36 and WHOQOL-BREF are available for international use, but it is not clear if they measure the same constructs. We compared the psychometric properties and factor structures of these two instruments. Data were collected from a national representative sample (n=11,440) in the 2001 Taiwan National Health Interview Survey, which included Taiwan versions of the SF-36 and WHOQOL-BREF. We used Cronbach's alpha coefficient to estimate scale reliability. We conducted exploratory factor analysis to determine factor structure of the scales, and applied multi trait analysis to evaluate convergent and discriminant validity. We used standardized effect size to compare known-groups validity for health-related variables (including chronic conditions and health care utilization) and self-reported overall quality of life. Structural equation modeling was used to analyze relationships among the two SF-36 component scales (PCS and MCS) and the four WHOQOL subscales (physical, psychological, social relations, and environmental). Cronbach's alpha coefficients were acceptable ([Symbol: see text]0.7) for all subscales of both instruments. The factor analysis yielded two unique factors: one for the 8 SF-36 subscales and a second for the 4 WHOQOL subscales. Pearson correlations were weak (<0.3) among subscales of both instruments. Correlations for subscales hypothesized to measure similar constructs differed little from those measuring heterogeneous subscales. Effect sizes suggested greater discrimination by the SF-36 for health status and services utilization known groups, but greater discrimination by the WHOQOL for QOL-defined groups. Structural equation modeling suggested that the SF-36 PCS and MCS were weakly associated with WHOQOL. In this Taiwan population sample, the SF-36 and WHOQOL-BREF appear to measure different constructs: the SF-36 measures health-related QOL, while the WHOQOL-BREF measures global QOL. Clinicians and researchers should carefully define their research questions related to patient-reported outcomes before selecting which instrument to use.

                Author and article information

                BMC Public Health
                BMC Public Health
                BMC Public Health
                BioMed Central (London )
                4 December 2014
                4 December 2014
                : 14
                : 1
                [ ]Division of Inborn Metabolic Diseases, Department of Pediatrics, Padua University Hospital, Padua, Italy
                [ ]Department of Cardiac, Thoracic and Vascular Sciences, Padua University Hospital, Padua, Italy
                [ ]Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
                [ ]Neurological Unit, St. Bassiano Hospital, Bassano del Grappa, Italy
                [ ]Department of Environmental Sciences, Biological and Pharmaceutical Technologies, Second University of Naples, Caserta, Italy
                [ ]CEINGE-Biotecnologie Avanzate S.c.a.r.l., Naples, Italy
                [ ]IRCCS SDN-Foundation, Naples, Italy
                © Cazzorla et al.; licensee BioMed Central Ltd. 2014

                This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated.

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