Moving Forward on Tumor Pathology Research Reporting: A Guide for Pathologists From the World Health Organization Classification of Tumors Living Evidence Gap Map by Tumour Type Group.

Evidence-based medicine (EBM) can be an unfamiliar territory for those working in tumor pathology research, and there is a great deal of uncertainty about how to undertake an EBM approach to planning and reporting histopathology-based studies. In this article, reviewed and endorsed by the Word Health Organization International Agency for Research on Cancer's International Collaboration for Cancer Classification and Research, we aim to help pathologists and researchers understand the basics of planning an evidence-based tumor pathology research study, as well as our recommendations on how to report the findings from these. We introduce some basic EBM concepts, a framework for research questions, and thoughts on study design and emphasize the concept of reporting standards. There are many study-specific reporting guidelines available, and we provide an overview of these. However, existing reporting guidelines perhaps do not always fit tumor pathology research papers, and hence, here, we collate the key reporting data set together into one generic checklist that we think will simplify the task for pathologists. The article aims to complement our recent hierarchy of evidence for tumor pathology and glossary of evidence (study) types in tumor pathology. Together, these articles should help any researcher get to grips with the basics of EBM for planning and publishing research in tumor pathology, as well as encourage an improved standard of the reports available to us all in the literature.

A New Hierarchy of Research Evidence for Tumor Pathology: A Delphi Study to Define Levels of Evidence in Tumor Pathology.

The hierarchy of evidence is a fundamental concept in evidence-based medicine, but existing models can be challenging to apply in laboratory-based health care disciplines, such as pathology, where the types of evidence and contexts are significantly different from interventional medicine. This project aimed to define a comprehensive and complementary framework of new levels of evidence for evaluating research in tumor pathology-introducing a novel Hierarchy of Research Evidence for Tumor Pathology collaboratively designed by pathologists with help from epidemiologists, public health professionals, oncologists, and scientists, specifically tailored for use by pathologists-and to aid in the production of the World Health Organization Classification of Tumors (WCT) evidence gap maps. To achieve this, we adopted a modified Delphi approach, encompassing iterative online surveys, expert oversight, and external peer review, to establish the criteria for evidence in tumor pathology, determine the optimal structure for the new hierarchy, and ascertain the levels of confidence for each type of evidence. Over a span of 4 months and 3 survey rounds, we collected 1104 survey responses, culminating in a 3-day hybrid meeting in 2023, where a new hierarchy was unanimously agreed upon. The hierarchy is organized into 5 research theme groupings closely aligned with the subheadings of the WCT, and it consists of 5 levels of evidence-level P1 representing evidence types that merit the greatest level of confidence and level P5 reflecting the greatest risk of bias. For the first time, an international collaboration of pathology experts, supported by the International Agency for Research on Cancer, has successfully united to establish a standardized approach for evaluating evidence in tumor pathology. We intend to implement this novel Hierarchy of Research Evidence for Tumor Pathology to map the available evidence, thereby enriching and informing the WCT effectively.

Evidence-based diagnostic accuracy measurement in urine cytology using likelihood ratios.

INTRODUCTION: Recent cytology classification systems have become more evidence-based and advocate for the use of risk of malignancy (ROM) as a measure of test performance. From the statistical viewpoint, ROM represents the post-test probability of malignancy, which changes with the test result and also with the prevalence of malignancies (or pre-test probability) in each individual practice setting and individual patient presentation. Evidence-based medicine offers likelihood ratios (LRs) as a measure of diagnostic accuracy for multilevel diagnostic tests, superior to sensitivity and specificity as data binarization and information loss are avoided. LRs are used in clinical medicine and could be successfully applied to the practice of cytopathology. Our aim was to establish LRs to compare diagnostic accuracy of The Paris System for Reporting Urinary Cytology (TPS) and of a historic urine cytology reporting system. MATERIALS AND METHODS: We analyzed sequential voided urine cytology cases with histologic outcomes: 188 pre-TPS and 167 post-TPS. LRs were calculated as LR = True positive % (per category)/False positive % (per category) [95% confidence interval] and interpreted LRs = 1 nondiagnostic, LR >1 favor, LR >10 strongly favor, LRs <1 favor exclusion, and LR <0.1 strongly favor exclusion of a target condition, respectively. CATmaker open source software and Fagan nomograms were used for calculation and visualization of the corresponding post-test probability (ROM) of high-grade urothelial carcinoma (HGUC) in various scenarios. RESULTS: Both reporting systems show near-similar performance in terms of LRs, with moderate discriminatory power of negative, suspicious, and positive for HGUC test results. The atypical urothelial cell (AUC) category establishes as indiscriminate LR = 1 in the TPS, whereas in pre-TPS it favored a benign condition. We further demonstrate the utility of LRs to determine individual post-test probability (ROM) in a variety of clinical scenarios in a personalized fashion. CONCLUSIONS: The LRs allow for a quantitative performance measure in case of urine cytology across different scenarios adding numeric information on diagnostic test accuracy and post-test probability of HGUC. The diagnostic accuracy of pre-TPS and post-TPS remained similar for all but the AUC category. With the TPS, the AUC category has become genuinely diagnostically and statistically indeterminate and requires further patient investigations.

Molecular subtype profiling of invasive breast cancers weakly positive for estrogen receptor.

The estrogen receptor (ER) is a key predictive biomarker in the treatment of breast cancer. There is uncertainty regarding the use of hormonal therapy in the setting of weakly positive ER by immunohistochemistry (IHC). We report intrinsic subtype classification on a cohort of ER weakly positive early-stage breast cancers. Consecutive cases of breast cancer treated by primary surgical resection were retrospectively identified from 4 centers that engage in routine external proficiency testing for breast biomarkers. ER-negative (Allred 0 and 2) and ER weakly positive (Allred 3-5) cases were included. Gene expression profiling was performed using qRT-PCR. Intrinsic subtype prediction was made based upon the PAM50 gene expression signature. 148 cases were included in the series: 60 cases originally diagnosed as ER weakly positive and 88 ER negative. Of the cases originally assessed as ER weakly positive, only 6 (10 %) were confirmed to be of luminal subtype by gene expression profiling; the remaining 90 % of cases were classified as basal-like or HER2-enriched subtypes. This was not significantly different than the fraction of luminal cases identified in the IHC ER-negative cohort (5 (5 %) luminal, 83(95 %) non-luminal). Recurrence-free, and overall, survival rates were similar in both groups (p = 0.4 and 0.5, respectively) despite adjuvant hormonal therapy prescribed in the majority (59 %) of weakly positive ER cases. Weak ER expression by IHC is a poor correlate of luminal subtype in invasive breast cancer. In the setting of highly sensitive and robust IHC methodology, cutoffs for ER status determination and subsequent systemic therapy should be revisited.