The OncoLifeS data-biobank for oncology: a comprehensive repository of clinical data, biological samples, and the patient\u2019s perspective

Grigory Sidorenkov,Jourik A Gietema,Janny Nagel,Marcel Nijland,Bert Van Der Vegt,Maaike H M Oonk,Coby Meijer,Klaas Havenga,Gyorgy B Halmos,John H Maduro,Gertruida H De Bock,Harry J M Groen,Max J H Witjes,Rene J Oostergo,Jacko J Duker

doi:10.1186/s12967-019-2122-x

Abstract

BackgroundUnderstanding cancer heterogeneity, its temporal evolution over time, and the outcomes of guided treatment depend on accurate data collection in a context of routine clinical care. We have developed a hospital-based data-biobank for oncology, entitled OncoLifeS (Oncological Life Study: Living well as a cancer survivor), that links routine clinical data with preserved biological specimens and quality of life assessments. The aim of this study is to describe the organization and development of a data-biobank for cancer research.ResultsWe have enrolled 3704 patients aged ≥ 18 years diagnosed with cancer, of which 45 with hereditary breast-ovarian cancer (70% participation rate) as of October 24th, 2019. The average age is 63.6 ± 14.2 years and 1892 (51.1%) are female. The following data are collected: clinical and treatment details, comorbidities, lifestyle, radiological and pathological findings, and long-term outcomes. We also collect and store various biomaterials of patients as well as information from quality of life assessments.ConclusionEmbedding a data-biobank in clinical care can ensure the collection of high-quality data. Moreover, the inclusion of longitudinal quality of life data allows us to incorporate patients’ perspectives and inclusion of imaging data provides an opportunity for analyzing raw imaging data using artificial intelligence (AI) methods, thus adding new dimensions to the collected data.

Highlights

Understanding cancer heterogeneity, its temporal evolution over time, and the outcomes of guided treatment depend on accurate data collection in a context of routine clinical care
Randomized clinical trials (RCTs) are generally considered the best approach for evaluating such treatment approaches, primarily because they reduce the risks of bias, the strict inclusion criteria limit their
We anticipate that approximately 1500 patients will be included in the data-biobank each year from 2019, with the total size expected to reach 10,000 participants by 2023

Summary

Introduction

Understanding cancer heterogeneity, its temporal evolution over time, and the outcomes of guided treatment depend on accurate data collection in a context of routine clinical care. We have developed a hospitalbased data-biobank for oncology, entitled OncoLifeS (Oncological Life Study: Living well as a cancer survivor), that links routine clinical data with preserved biological specimens and quality of life assessments. The aim of this study is to describe the organization and development of a data-biobank for cancer research. Cancer has Cancer is a complex disease with more than 1 million known genotypes [4]. Patients with cancer often differ genotypically and phenotypically [5], resulting in marked variabilities in the required management and treatment response. Randomized clinical trials (RCTs) are generally considered the best approach for evaluating such treatment approaches, primarily because they reduce the risks of bias, the strict inclusion criteria limit their

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