Advancing maturity modeling for precision oncology

Introduction

This study aimed to map the maturity of precision oncology as an example of a Learning Health System by understanding the current state of practice, tools and informatics, and barriers and facilitators of maturity.

Methods

We conducted semi-structured interviews with 34 professionals (e.g., clinicians, pathologists, and program managers) involved in Molecular Tumor Boards (MTBs). Interviewees were recruited through outreach at 3 large academic medical centers (AMCs) (n = 16) and a Next Generation Sequencing (NGS) company (n = 18). Interviewees were asked about their roles and relationships with MTBs, processes and tools used, and institutional practices. The interviews were then coded and analyzed to understand the variation in maturity across the evolving field of precision oncology.

Results

The findings provide insight into the present level of maturity in the precision oncology field, including the state of tooling and informatics within the same domain, the effects of the critical environment on overall maturity, and prospective approaches to enhance maturity of the field. We found that maturity is relatively low, but continuing to evolve, across these dimensions due to the resource-intensive and complex sociotechnical infrastructure required to advance maturity of the field and to fully close learning loops.

Conclusion

Our findings advance the field by defining and contextualizing the current state of maturity and potential future strategies for advancing precision oncology, providing a framework to examine how learning health systems mature, and furthering the development of maturity models with new evidence.

Implementation of Precision Oncology in Clinical Practice: Results of a National Survey for Health Care Professionals

BACKGROUND

Two main aspects lead the implementation of precision oncology into clinical practice: the adoption of extended genome sequencing technologies and the institution of the Molecular Tumor Boards (MTBs). CIPOMO (Italian Association of Heads of Oncology Department) promoted a national survey across top health care professionals to gain an understanding of the current state of precision oncology in Italy.

METHODS

Nineteen questions were sent via the SurveyMonkey platform to 169 heads of oncology departments. Their answers were collected in February 2022.

RESULTS

Overall, 129 directors participated; 113 sets of answers were analyzed. Nineteen regions out of 21 participated as a representative sample of the Italian health care system. The use of next-generation sequencing (NGS) is unevenly distributed; informed consent and clinical reports are managed differently, as the integration of medical, biologic, and informatics domains in a patient-centered workflow is inconsistent. A heterogeneous MTB environment emerged. A total of 33.6% of the responding professionals did not have access to MTBs while 76% of those who have did not refer cases.

CONCLUSIONS

NGS technologies and MTBs are not homogeneously implemented in Italy. This fact potentially jeopardizes equal access chances to innovative therapies for patients. This survey was carried out as part of an organizational research project, pursuing a bottom-up approach to identify the needs and possible solutions to optimize the process. These results could be a starting point for clinicians, scientific societies, and health care institutions to outline the best practices and offer shared recommendations for precision oncology implementation in current clinical practice.

A virtual molecular tumor board to improve efficiency and scalability of delivering precision oncology to physicians and their patients

OBJECTIVES

Scalable informatics solutions that provide molecularly tailored treatment recommendations to clinicians are needed to streamline precision oncology in care settings.

MATERIALS AND METHODS

We developed a cloud-based virtual molecular tumor board (VMTB) platform that included a knowledgebase, scoring model, rules engine, an asynchronous virtual chat room and a reporting tool that generated a treatment plan for each of the 1725 patients based on their molecular profile, previous treatment history, structured trial eligibility criteria, clinically relevant cancer gene-variant assertions, biomarker-treatment associations, and current treatment guidelines. The VMTB systematically allows clinician users to combine expert-curated data and structured data from clinical charts along with molecular testing data to develop consensus on treatments, especially those that require off-label and clinical trial considerations.

RESULTS

The VMTB was used as part of the cancer care process for a focused subset of 1725 patients referred by advocacy organizations wherein resultant personalized reports were successfully delivered to treating oncologists. Median turnaround time from data receipt to report delivery decreased from 14 days to 4 days over 4 years while the volume of cases increased nearly 2-fold each year. Using a novel scoring model for ranking therapy options, oncologists chose to implement the VMTB-derived therapies over others, except when pursuing immunotherapy options without molecular support.

DISCUSSION

VMTBs will play an increasingly critical role in precision oncology as the compendium of biomarkers and associated therapy options available to a patient continues to expand.

CONCLUSION

Further development of such clinical augmentation tools that systematically combine patient-derived molecular data, real-world evidence from electronic health records and expert curated knowledgebases on biomarkers with computational tools for ranking best treatments can support care pathways at point of care.