Date Published: July 29, 2020
Publisher: Springer International Publishing
Author(s): Yassine Kamal Lyauk, Trine Meldgaard Lund, Andrew C. Hooker, Mats O. Karlsson, Daniël M. Jonker.
In clinical trials within lower urinary tract symptoms due to benign prostatic hyperplasia (BPH-LUTS), the International Prostate Symptom Score (IPSS) is commonly the primary efficacy outcome while the Quality of Life (QoL) score and the BPH Impact Index (BII) are common secondary efficacy markers. The current study aimed to characterize BPH-LUTS progression using responses to the IPSS, the QoL, and the BII in an integrated item response theory (IRT) framework and assess the Fisher information of each scale. The power of this approach to detect a drug effect was compared with an IRT approach considering only IPSS responses. A unidimensional and a bidimensional pharmacometric IRT model, based on item-level IPSS responses in a clinical trial with 403 patients, were extended by incorporating patients’ QoL and summary BII scores over the 6-month trial period. In the developed unidimensional integrated model, the QoL score was found to be the most informative, representing 17% of the total Fisher information, while the combined information content of the seven IPSS items represented 70.6%. In the bidimensional model, “storage” and both storage and “voiding” disability drove QoL and summary BII responses, respectively. Sample size reduction of 16% to detect a drug effect at 80% power was obtained with the unidimensional integrated IRT model compared with its counterpart IPSS IRT model. This study shows that utilizing the information content across the IPSS, QoL, and BII scales in an integrated IRT framework results in a modest but meaningful increase in power to detect a drug effect.
As the prostate enlarges with age, older men may suffer from the obstruction of the prostatic urethra and deterioration of the urethral sphincter function (1). This condition is known as benign prostate hyperplasia (BPH) and is estimated to affect 50% of the male population by age 60 years (2,3). Lower urinary tract symptoms (LUTS) often develop due to BPH and are thought to stem from a combination of both static and dynamic factors of BPH as well as the bladder’s response to outflow obstruction (4,5). The prevalence of BPH-LUTS is similar across different countries (6–11) and can hence be considered a medical condition with a substantial impact on public health globally speaking.
The CS36 trial enrolled 403 patients, of which 369 completed the six-month treatment period. The baseline patient population characteristics have been presented elsewhere (21). A total of 21,836 item-level IPSS, 3119 QoL scores, and 1116 BIIsummary observations over the 6-month trial period were available for analysis in the current work. Figure 1 shows the mean time course for the total IPSS, the QoL score, and the BII, respectively, in the CS36 trial. A marked drop in mean score was observed for all treatment arms on each BPH-LUTS scale and no dose-response relationship was apparent on any of the three scales. The Supplemental Material contains further details on the distribution of responses in each BPH-LUTS scale.Fig. 1Time course of the mean total International Prostate Symptom Score, Quality of Life score, and summary Benign Prostatic Hyperplasia Impact Index. Standard errors are indicated as error bars
The current paper presents models integrating multiple BPH-LUTS scales using IRT. To our knowledge, this is the first model integrating several endpoints within the therapeutic area. We investigated the information content within different BPH-LUTS measures and compared the power to detect a treatment effect of the integrated IRT approach with a previously developed IRT models that considered only IPSS responses. Assessing the effect of drugs on the voiding and storage IPSS subscores is common practice in BPH-LUTS clinical trials although its clinical meaningfulness is not established (13,23,35–37). A previous longitudinal bidimensional IRT model, based on item-level IPSS, aimed to reflect this type of analysis while preserving item-level information (21); in the current work, this model was further extended by including data from the QoL and BII scales. This allowed further characterization of underlying disability and differentiation of the effect of treatment on the “generalized” voiding and storage latent variables, respectively.
IRT modeling was used to integrate data from multiple disease-specific PRO endpoints within BPH-LUTS into a single model. A sample size reduction of 16% to detect a drug effect at 80% power was obtained with the unidimensional integrated IRT model compared with its counterpart IPSS IRT model. This study shows that utilizing the information content across IPSS, QoL, and BII scales in an integrated IRT framework results in a modest but meaningful increase in power to detect a drug effect.