Triple AIM1

Dr. Jean-Paul A. van Basten


Create an infrastructure that maps routine clinical outcomes, costs and QoL in order to offer a more tailor-made therapy to men with metastatic hormone sensitive prostate cancer.


Background and rationale

Treatment strategies for metastatic hormone sensitive prostate cancer (mHSPC) evolve rapidly as survival outcomes of androgen deprivation therapy (ADT) consisting of bilateral orchiectomy, luteinizing hormone-releasing agonist or receptor antagonist, appeared inferior to those of ADT combined with either docetaxel, abiraterone, local radiotherapy or apalutamide. Given this rapidly evolving treatment landscape, there is a need for more detailed insights in real world data reflecting why treatments are initiated, combined and sequenced, how patients experience their quality of life (QoL) and how their relative effectiveness profiles emerge outside of clinical trial setting as well as their cost-effectiveness profiles.

Aim and relevance of TripleAiM1

In daily practice, routine clinical outcomes as well as costs and QoL are rarely measured and recorded as the infrastructure for thorough measurement and data collection is (often) lacking.  Therefore, this study aims to facilitate this infrastructure to understand the optimal indication and use of treatments for mHSPC, the cost-effectiveness and to evaluate the impact of these treatments on patient outcome (relevant clinical outcome and QoL) in mHSPC patients with the aim to offer a more tailor-made therapy based on optimizing patient value.

Patient description:

Patients ≥18 years with newly diagnosed mHSPC are eligible for inclusion in the TripleAiM1 study.


1. Infrastructure:

An infrastructure has been developed in which clinical results, patient reported outcome (PRO) and costs data can be measured, collected and analysed in a uniform manner beyond the full care cycle of individual patients. The clinical and cost data are extracted from existing data sources. A  dashboard is available for all participating hospitals with access to their own data collection and benchmark data.

This infrastructure has the potential to evolve to an (eco)system in which valuable learning cycles can be implemented.

2. Design of protocol:

The protocol is designed for an observational prospective study.

Protocol defined information:

  • Medical condition
  • Subset of parameters to measure patient relevant outcome (Diagnostic, clinical parameters, Pro’s and Costs)
  • Data measurement methods
  • Statical analysis

Size and scope:

  • 15 hospitals
  • 450 patients
  • Inclusion criteria: newly diagnosed mHSCP patients, ≥ 18 years
  • Measure and collect Patient relevant outcomes ( Clinical, PRO’s )and Cost data
  • Data analysis on individual patient level/ therapy group level

Most important (preliminary) results

  • The infrastructure to measure and collect data in a unified way across all hospitals is built, as well as the central data base which are already in use, including the database dashboard.
  • Retrospective data from 5 hospitals are available in the dashboard and will provide first insights into diagnostics and diagnosis, treatment (sequence), patient relevant clinical outcomes and costs.
  • Patient inclusion in the prospective observational study has started and patient dashboard on PRO’s  is in place
  • Four working groups will focus on the following themes: 1) diagnosis and clinical treatment, 2) patient engagement, 3) Value Based Health Care and 4) sustainability and health care optimalization