Delivery of high-quality healthcare is intrinsically linked to accurate and timely diagnoses, a cornerstone especially critical in cancer care. Diagnostic tests in oncology are not merely procedures; they are fundamental in shaping treatment plans, informing prognosis, predicting treatment response, and monitoring disease progression and recurrence. Pathologists, with their specialized knowledge, are indispensable members of the oncology team. Their expertise guides the selection, execution, and interpretation of diagnostic tests, ensuring that results and their implications are effectively communicated to inform subsequent care decisions.
This article, drawing upon discussions from a workshop hosted by the National Cancer Policy Forum, reviews the existing challenges in pathology. It further highlights practical strategies aimed at enhancing the quality of cancer diagnosis and care by improving patient access to specialized expertise in oncologic pathology.
Challenges in Modern Cancer Diagnosis
The landscape of cancer diagnosis and care is being reshaped by the advent of sophisticated diagnostic testing and the expansion of precision therapies. The traditional model, where clinicians ordered tests and pathologists provided results, is evolving. Today, clinicians face an overwhelming array of diagnostic testing options, often with limited evidence-based guidelines and clinical decision support (CDS) to navigate test selection and interpretation. For instance, in lung cancer, numerous molecular, cytogenetic, and immunohistochemical tests act as companion diagnostics for various targeted therapies. Laboratories utilize diverse platforms for these tests, which can lead to variations in outputs and interpretative thresholds. Test selection itself is further nuanced by histologic subtype, disease stage, and treatment response.
Furthermore, contemporary diagnostic tests often yield complex results that are not simple binary outcomes. They may lack universally accepted reference ranges, making expert interpretation essential for guiding clinical decisions. Cancer prevention strategies also add complexity, requiring an understanding of which cancer detection tests, used alone or with primary prevention methods like vaccines, are most effective at different ages and how to manage abnormal results based on individual risk profiles. Cervical cancer prevention stands as a prime example of this complex approach.
Diagnostic pathology reports now integrate a multitude of data types, extending beyond morphology to include mRNA expression, genomic DNA data, histology, and immunohistochemical findings. Molecular testing has significantly increased the complexity of cancer diagnosis and care by delineating numerous cancer subtypes, like the over 150 subtypes in hematopoietic neoplasms, each identifiable by specific molecular abnormalities. This refined classification enables the selection of precision oncology therapies targeting these specific abnormalities. The complexity is further amplified by the shift from single-gene to multiplex “omics” panels encompassing hundreds of genes. To harness the clinical potential of these extensive datasets, integrated information management systems are being developed. These systems aim to incorporate structured genomic sequence data into secure, interoperable electronic health record (EHR) platforms. Deployed primarily in large, tertiary care settings, these systems facilitate data integration into comprehensive reports, often discussed in multidisciplinary tumor boards. However, widespread adoption of such systems remains a future aspiration, not yet realized in most cancer care environments.
Diagnostic uncertainty, interobserver variability, and potential errors due to the subjective nature of test interpretation are often underestimated aspects of pathology. Like all medical fields, pathology has its “gray zones.” Accuracy can be improved and nondefinitive diagnoses minimized through correlation with clinical and radiologic findings, ancillary tests, and second opinion reviews. For example, a study on surgical pathology second opinions revealed major diagnostic disagreements in 2.3% of cases and minor disagreements in 9.0%. The level of training and skill can vary across different practice settings. Even pathologists with subspecialty training may not maintain expertise if practicing as generalists in non-academic environments.
Communicating complex diagnostic results to patients and clinicians unfamiliar with emerging technologies is another significant challenge. Effective and timely diagnosis can be hindered by EHR system interoperability issues and insufficient collaboration and communication among pathologists, radiologists, and oncologists within a patient’s care team.
Disparities in patient access to pathology expertise and advanced technologies can significantly impact the speed and precision of cancer diagnosis, thereby affecting the quality of care. Smaller community hospitals, particularly in underserved areas, may lack pathologists with specialized training in oncologic pathology, as well as the necessary support, equipment, and resources for complex diagnostic testing and interpretation required for precision oncology. Technological advancements can also exacerbate health disparities, as resource-limited facilities may lag in adopting new technologies, leading to inequities in patient care. Furthermore, the high cost of many novel tests and technologies can restrict access, especially when payer coverage is initially limited.
Potential Solutions for Enhancing Cancer Diagnosis
Addressing the challenges in cancer diagnosis and care requires proactive strategies from leaders in pathology and the broader healthcare community. Improving patient access to expertise in cancer diagnostics can be achieved through several key approaches: enhanced collaboration among pathologists, radiologists, oncologists, and informaticians; improved education and training, including initial and continuous certification; greater utilization of expert consultations, incorporating whole-slide imaging and teleconsultation; and broader dissemination of appropriate clinical CDS tools.
The increasing convergence of radiology and pathology, along with advancements in bioinformatics, presents a significant opportunity to enhance diagnostic oncology. Integrating pathology and radiology reports in oncology could provide a more cohesive and comprehensive understanding of a patient’s disease, its implications for treatment planning, management, and response monitoring. For example, at Memorial Sloan Kettering Cancer Center, integrated reports are generated for bone cancer patients through tumor boards. Increased use of multispecialty tumor conferences is crucial for fostering interdisciplinary collaboration. However, these conferences are time-intensive and require the involvement of multiple specialists. Current reimbursement models and clinical work cultures often do not adequately support this type of inter-specialty teamwork. New payment models, such as the Merit-Based Incentive Payment System, and innovative informatics technologies could incentivize and facilitate the integration of patient-centric diagnostic reports.
Creating a new integrative medical specialty in diagnostic oncology, encompassing training in pathology, radiology, cancer biology, and computational methods, offers another avenue to cultivate specialized diagnostic expertise in cancer. Developing a comprehensive digital architecture supporting pathology, radiology, and informatics could be instrumental in unifying diagnostic training programs. Further enhancements to education and training include adopting entrustable professional activities, which are observable, measurable work units that better reflect clinical practice competencies compared to traditional training metrics. Surveys of pathology residents indicate a need for greater emphasis on molecular and genomic diagnostics and pathology informatics in training programs. The American Board of Medical Specialties and the American Board of Pathology prioritize improving methods for continuous physician education, focusing on “assessment of learning, for learning,” to ensure physicians remain current with rapid healthcare advancements.
For pathologists in community practices who may lack access to cutting-edge diagnostic technologies and struggle to stay updated in rapidly evolving fields, telemedicine and expert consultation are vital. Telemedicine, clinician-to-clinician teleconsulting, and telementoring partnerships can effectively disseminate knowledge and build capacity in regions lacking specialized medical care. Digitization is transforming pathology, facilitating telemedicine and expert consultations. The FDA’s approval of the first digital pathology system for reviewing whole-slide images marks a significant step. Institutions are increasingly adopting real-time digital pathology strategies, including telepathology, both internally and for external expert consultations. This approach aligns with recommendations to enhance pathology report accuracy through second reviews for selected cases.
Clinical decision support (CDS) tools are essential for helping clinicians appropriately order, interpret, and utilize diagnostic test results. Diagnostic management teams can develop standardized test ordering algorithms that reflect optimal diagnostic pathways for specific diseases. This involves collaboration among diagnostic testing experts, treating clinicians, and biomedical informaticians to create and refine these algorithms, and to produce evidence-based, integrated diagnostic data reports that guide treatment and disease monitoring.
Artificial intelligence (AI) applications offer promising solutions to manage the cognitive overload from complex diagnostic information. In digital pathology, AI can highlight areas of interest in specimens, enabling pathologists to focus on potentially critical lesions. Studies have shown that deep-learning algorithms can effectively detect lymph node metastases in breast cancer patients. Digitization in pathology also enables the creation of large digital pathology datasets, which can be analyzed with AI to develop and validate computational diagnostic methods.
As precision oncology evolves, the crucial role of precise diagnostics in guiding patient care decisions is amplified. The potential negative consequences of limited access to high-quality oncologic pathology and integrated diagnostics cannot be overlooked. Policy makers and leaders in pathology and oncology must take decisive action to address these critical gaps in cancer care and ensure equitable access to improved cancer diagnosis and care for all patients.
