26 research outputs found
A model to predict disease progression in patients with autosomal dominant polycystic kidney disease (ADPKD): the ADPKD Outcomes Model.
Background: Autosomal dominant polycystic kidney disease (ADPKD) is the leading inheritable cause of end-stage
renal disease (ESRD); however, the natural course of disease progression is heterogeneous between patients. This study
aimed to develop a natural history model of ADPKD that predicted progression rates and long-term outcomes in patients
with differing baseline characteristics.
Methods: The ADPKD Outcomes Model (ADPKD-OM) was developed using available patient-level data from the placebo
arm of the Tolvaptan Efficacy and Safety in Management of ADPKD and its Outcomes Study (TEMPO 3:4; ClinicalTrials.gov
identifier NCT00428948). Multivariable regression equations estimating annual rates of ADPKD progression, in terms of
total kidney volume (TKV) and estimated glomerular filtration rate, formed the basis of the lifetime patient-level simulation
model. Outputs of the ADPKD-OM were compared against external data sources to validate model accuracy and
generalisability to other ADPKD patient populations, then used to predict long-term outcomes in a cohort matched to
the overall TEMPO 3:4 study population.
Results: A cohort with baseline patient characteristics consistent with TEMPO 3:4 was predicted to reach ESRD at a mean
age of 52 years. Most patients (85%) were predicted to reach ESRD by the age of 65 years, with many progressing to
ESRD earlier in life (18, 36 and 56% by the age of 45, 50 and 55 years, respectively). Consistent with previous research and
clinical opinion, analyses supported the selection of baseline TKV as a prognostic factor for ADPKD progression, and
demonstrated its value as a strong predictor of future ESRD risk. Validation exercises and illustrative analyses confirmed
the ability of the ADPKD-OM to accurately predict disease progression towards ESRD across a range of clinically-relevant
patient profiles.
Conclusions: The ADPKD-OM represents a robust tool to predict natural disease progression and long-term outcomes in
ADPKD patients, based on readily available and/or measurable clinical characteristics. In conjunction with clinical
judgement, it has the potential to support decision-making in research and clinical practice
Undergoing Diagnostic Evaluation for Possible Cancer Affects the Health-Related Quality of Life in Patients Presenting with Non-Specific Symptoms.
AIM:Undergoing diagnostic evaluation for possible cancer can affect health-related quality of life (HRQoL). The aims of this study were to examine the HRQoL in patients undergoing a diagnostic evaluation for possible cancer due to non-specific symptoms and further to investigate the impact of socio-demographic and medical factors associated with HRQoL at the time of diagnosis. METHODS:This was a prospective, multicenter survey study that included patients who were referred for a diagnostic evaluation due to non-specific cancer symptoms. Participants completed the EORTC-QLQ-C30 quality of life scale before and after completing the diagnostic evaluation. The baseline and follow-up EORTC-QLQ-C30 scores were compared with reference populations. The impact of socio-demographic and medical factors on HRQoL at follow-up was explored by bootstrapped multivariate linear regression. RESULTS:A total of 838 patients participated in the study; 680 (81%) also completed follow-up. Twenty-two percent of the patients received a cancer diagnosis at the end of follow-up. Patients presented initially with a high burden of symptoms, less role and emotional functioning and a lower global health/QoL. Most domains improved after diagnosis and no clinically important difference between baseline and follow-up scores was found. Patients reported effects on HRQoL both at baseline and at follow-up compared with the Danish reference population and had similar scores as a cancer reference population. Co-morbidity, being unemployed and receiving a cancer diagnosis had the greatest effect on HRQoL around the time of diagnosis. CONCLUSIONS:Patients with non-specific symptoms reported an affected HRQoL while undergoing a diagnostic evaluation for possible cancer. Morbidity, being unemployed and receiving a cancer diagnosis had the greatest effect on HRQoL around the time of diagnosis