International REgistry of COnservative or Radical Treatment of Localized Kidney Tumors

Study design

The overall objective of the i-RECORD project is to build a multicentre multi-arm multi-stage prospective observational registry collecting data on the management of kidney cancer in consecutive patients treated at 50 tertiary referral Centers worldwide over a 2 years-period and with 5 years of follow-up

. On this registry, six prospective trials with specific objectives have been built.

The i-RECORd project is designed as an observational prospective longitudinal trial involving 50 international, very-high-volume tertiary referral Centers with extensive experience in management of kidney cancer. Centers will be included in the project only if they will be able to certify at least to: 1) perform 150 partial and radical nephrectomy/year, or 2) to perform 80 ATs/year, or 3) to include 50 patients in WW/AS protocols/year.

The enrollment and follow-up periods will be 2 and 5 years, respectively. The estimate of patients' enrollment over the study period is 10'000 inclusions.

The 50 Centers finally enrolled in the i-RECORD project will be given the access to a web-based platform for data collection for 24 months from the starting date of the project.

A web-based e-form platform will be used for data collection.

Data collection

This observational study aims to obtain controlled, qualitative and quantitative, data of the enrolled patients through a web-based e-form platform. For all patients it will be asked to complete a data collection form specifically designed for this study, consisting of some subfolders:

1. Anthropometric, pre-operative and comorbidity data (patient characteristics).

2. Imaging data e and pre-operative tumor features (tumor characteristics).

3. Intra-operative and post-operative data (treatment characteristics).

4. Histopathological analysis (tumor histopathological characteristics).

5. Patients follow-up variables (at 6, 12, 24 and 60 months from the treatment) (follow-up characteristics).

Decision Analysis Modeling

Beyond traditional descriptive and inferential statistical analyses, the i-RECORd project will provide a comprehensive overview of the current selection criteria for each type of management option by applying innovative statistical methods (Decision Analysis Modeling through discrete choice models) to determine the differential impact of all potential relevant variables on the choice of treatment. To do so, we will consider specific clinical scenarios (clinical clusters) made of the integration of patient characteristics (comorbidity score, performance status, age, gender, etc.), patient-reported outcomes measures (PROMs), tumors anatomical features (degree of complexity, clinical diameter, side, location within the kidney, involvement of renal sinus or collecting system, etc.), surgeon-related factors (surgical experience and background), hospital economic availabilities (i.e. open, laparoscopic, robotic surgery) and other country-specific socio-economical features in order to determine the impact of such variables on the final choice of treatment.

By applying the discrete choice model to the analysis of the prospective dataset, the i-RECORd project will overcome the current state of the art in the treatment of localized renal tumors as it will show how the choice of treatment is performed by the decision-maker (at a surgeon- and hospital-level) in each specific clinical cluster of patients, why that choice was performed according to a careful analysis of the personalized patient setting and whether that choice will influence the postoperative outcomes.

Adapted MAMS Registry

The i-RECORD will be designed adapting the innovative concept of multi-arm, multi-stage (MAMS) platform randomized trials (used, for instance, for the design of the Systemic Therapy in Advancing or Metastatic Prostate cancer: Evaluation of Drug Efficacy (STAMPEDE) Trial) to create a dynamic, observational registry evaluating simultaneously different management options in different patient- and/or tumor-related scenarios.