PROMISE: a real-world clinical-genomic database to address knowledge gaps in prostate cancer

Abstract

Purpose Prostate cancer is a heterogeneous disease with variable clinical outcomes. Despite numerous recent approvals of novel therapies, castration-resistant prostate cancer remains lethal. A “real-world” clinical-genomic database is urgently needed to enhance our characterization of advanced prostate cancer and further enable precision oncology. Methods The Prostate Cancer Precision Medicine Multi-Institutional Collaborative Effort (PROMISE) is a consortium whose aims are to establish a repository of de-identified clinical and genomic patient data that are linked to patient outcomes. The consortium structure includes a (1) bio-informatics committee to standardize genomic data and provide quality control, (2) biostatistics committee to independently perform statistical analyses, (3) executive committee to review and select proposals of relevant questions for the consortium to address, (4) diversity/inclusion committee to address important clinical questions pertaining to racial disparities, and (5) patient advocacy committee to understand patient perspectives to improve patients’ quality of care. Results The PROMISE consortium was formed by 16 academic institutions in early 2020 and a secure RedCap database was created. The first patient record was entered into the database in April 2020 and over 1000 records have been entered as of early 2021. Data entry is proceeding as planned with the goal to have over 2500 patient records by the end of 2021. Conclusions The PROMISE consortium provides a powerful clinical-genomic platform to interrogate and address data gaps that have arisen with increased genomic testing in the clinical management of prostate cancer. The dataset incorporates data from patient populations that are often underrepresented in clinical trials, generates new hypotheses to direct further research, and addresses important clinical questions that are otherwise difficult to investigate in prospective studies.

Ethnic Pharmacogenomic Differences in the Management of Asian Patients with Metastatic Prostate Cancer

“…As mentioned, there is increasing evidence that germline mutations contribute to the risk of PC, some of which are also actionable [ 61 ]. Repositories of clinical and genomic data, such as the Prostate Cancer Precision Medicine Multi-Institutional Collaborative Effort (PROMISE) [ 62 ], will help to enable precision oncology. Local and regional data will be needed to document relevant hotspot mutations, and to characterise variants of uncertain significance, perhaps in a manner similar to those for hereditary breast and ovarian cancers [ 63 ].…”

Clinical annotations for prostate cancer research: Defining data elements, creating a reproducible analytical pipeline, and assessing data quality

“…Data extraction had to be scalable to thousands of patient records without external funding, precluding desirable approaches such as blinded parallel annotation by more than one person. Earlier versions of the database have already been useful to assess genomic and clinical features in prostate cancer, 15–17 as are similar databases 6,18,19 . Unsurprisingly, for some data elements, reproducibility of annotations was suboptimal, including for data elements known to have low reproducibility, like tumor T stage 20 .…”

“…Earlier versions of the database have already been useful to assess genomic and clinical features in prostate cancer, [15][16][17] as are similar databases. 6,18,19 Unsurprisingly, for some data elements, reproducibility of annotations was suboptimal, including for data elements known to have low reproducibility, like tumor T stage. 20 Besides suboptimal reproducibility, completeness of T stage for both annotations was low in the subset of patients selected for the reproducibility study, who all had metastatic disease.…”

Ki-67, topoisomerase IIα and miR-221 have a limited prostate cancer risk stratification ability on a medium-term follow-up: results of a high-risk radical prostatectomy cohort

“…Also, efforts must be made in increasing our genomic knowledge of PCa, as it is for breast and other cancers. In this sense “real-world” clinical-genomic database and platforms are being created and are already available to enhance high risk and advanced PCa characterisation, paving the way towards precision oncology and personalised care ( 49 , 50 ).…”