The PRISSMM™ cancer data modeling system, enhanced by and licensed from Memorial Sloan Kettering Cancer Center (MSK), is a state-of-the-art data modeling system that allows users to curate clinical information and calculate real-world cancer treatment outcomes in a consistent, reproducible manner. Now available for commercial licensing.
How Data Modeling Delivers Value in the Healthcare Sector
Data modeling is the process of analyzing and defining various types of data—sometimes referred to as big data—in order to identify and learn from meaningful patterns, fuel research and innovation, and improve communications and collaborations between key stakeholders, along with other goals.
Within the healthcare sector, pathbreaking developments in data modeling offer the potential for big data analytics to help clinicians better identify which patients would benefit from particular treatments or lifestyle changes, resulting in improved outcomes and enhanced healthcare efficiencies.
For companies involved in developing and testing new therapeutics or utilizing digital health tools to improve patient outcomes, data modeling can be a valuable way to aggregate and synthesize essential healthcare data. Data modeling can aid in evaluating new or existing compounds, designing and refining clinical trials, and planning and implementing other essential stages of drug development.
The PRISSMM™ System—a Unique Data Modeling System Focused on Cancer Outcomes
Precision medicine holds tremendous potential for cancer patients, and yet there is so much still to be achieved. Until now, life sciences, digital health, and other healthcare companies have been handicapped by a dearth of detailed, real-world clinical data about cancer treatment outcomes. This has prevented researchers from unlocking the potential of big data to most fully evaluate cancer treatments in the context of the rapidly expanding field of genomics.
The PRISSMM™ system is a standard taxonomy for classification and communication of structured information about cancer status and treatment outcomes, following specification of baseline information for patients with solid tumors. Each letter in “PRISSMM” corresponds to a dimension of cancer status or treatment response, including pathological (P) and radiological (R) evidence of locoregional or distant tumor.
The PRISSMM™ system enables MSK’s licensing partners to achieve four important objectives:
- Better communicate real-world outcomes in a consistent manner
- Expedite and optimize human curation of data model records
- Enable machine curation of medical records
- Build capacity to create, share, and use real-world data through a “lingua franca” understood throughout the oncology community
The PRISSMM™ System’s Key Features and Benefits
The PRISSMM™ system provides oncology researchers in commercial or academic settings with an invaluable new tool: a scientifically rigorous, reliable method for translating real-world data into real-world evidence about cancer outcomes. It offers a standardized communication method for describing any cancer patient’s status at any point throughout the disease trajectory, and for identifying and understanding large-scale implications of collective information in order to learn from all patients.
Effective data modeling depends upon the quality of clinical annotation, which in turn depends upon quality data standards. The PRISSMM™ system’s state-of-the-art data standards provide clear directives for human abstractors and a well-structured curricula to support machine learning and therefore, computer-assisted abstraction.
The data collected within the PRISSMM™ system starts at the patient level, and includes information from pathology reports, imaging reports of primary and distant tumor sites, biomarkers, and clinical impressions and plans. The PRISSMM™ system enables calculation of salient cancer treatment outcomes including:
- Time to discontinuation (TTD) of each anti-neoplastic drug
- TTD of any component in each anti-neoplastic regimen
- TTD of all components of each anti-neoplastic regiment
- Time to recurrence (TTR)
- Time to progression (TTP)
- Disease-free survival (DFS)
- Progression-free survival (PFS)
Benefits Tailored to the Needs of Every Project—and Licensing Partner
The oncology community—including life sciences and digital health corporations, clinicians, and academic researchers—requires open-source, transparent phenomic data standards and a reliable communication system to unlock the treasure trove of information contained in Electronic Health Record (EHR) systems.
The PRISSMM™ system offers that solution, thanks in part to its rigorous, standardized directives relating to data curation tasks starting from the initial date of a first cancer diagnosis. Data fields leverage existing standard ontologies and structured data sources, including NAACCR, which allows users to transfer structured data from EHR into their project database, reducing manual curation time.
For users, the PRISSMM™ system offers some meaningful advantages in comparison to RECIST (Response Evaluation Criteria in Solid Tumors), which is currently used in many clinical trials and FDA regulatory submissions. For example, RECIST requires like-scan-to-like-scan comparisons, and depends upon scans performed at pre-defined intervals—both conditions that often do not prevail in real-world contexts.
The original PRISSMM™ system was developed by Dr. Deborah Schrag, Chair of MSK’s Department of Medicine, while she was previously at Dana-Farber. MSK has enhanced the PRISSMM™ system, and, through an arrangement with Dana-Farber, is now the exclusive licensor of the PRISSMM™ system, offering it through commercial licenses and academic-research licenses.
Licensing partners may customize their real-world outcome data based upon project needs and focus. TTR, TTP, DFS, and PFS can each be defined using real-world outcome metrics customized to key project questions. Metrics may be curated, for example, across a particular type of cancer, or subset of patients (such as all patients with a specific biomarker).
To License the PRISSMM™ System or Learn More
Contact Chelsea Nichols, PRISSMM Project Manager, Translational Research Administration, Collaborative Research Center (CRC) Initiatives, MSK, email: [email protected]