Abstract

BackgroundMetastases play a role in about 90% of cancer deaths. Markers of epithelial-mesenchymal transition (EMT) measured in primary tumor cancer cells might provide diagnostic information about the likelihood that cancer cells have detached from the primary tumor. Used together with established diagnostic tests of detachment—lymph node evaluation and radiologic imaging—EMT marker measurements might improve the ability of clinicians to assess the patient’s risk of metastatic disease. Translation of EMT markers to clinical use has been hampered by a lack of valid analyses of clinically-informative parameters. Here, we demonstrate a rigorous approach to estimating the sensitivity, specificity, and prediction increment of an EMT marker to assess cancer cell detachment from primary tumors.MethodsWe illustrate the approach using immunohistochemical measurements of the EMT marker E-cadherin in a set of colorectal primary tumors from a population-based prospective cohort in North Carolina. Bayesian latent class analysis was used to estimate sensitivity and specificity in a setting of multiple imperfect diagnostic tests and no gold standard. Risk reclassification analysis was used to assess the extent to which addition of the marker to the panel of established diagnostic tests would improve mortality prediction. We explored how changing the latent class conditional dependence assumptions and definition of marker positivity would impact the results.ResultsAll diagnostic accuracy and prediction increment statistics varied with the choice of cut point to define marker positivity. When comparing different definitions of marker positivity to each other, numerous trade-offs were observed in terms of sensitivity, specificity, predictive discrimination, and prediction model calibration. We then discussed several implementation considerations and the plausibility of analytic assumptions.ConclusionsThe approaches presented here can be extended to any EMT marker, to most forms of cancer, and to different kinds of EMT marker measurements, such as RNA or gene methylation data. These methods provide valid, clinically-informative assessment of whether and how to use a given EMT marker to refine tumor staging and consequent treatment decisions.

Highlights

  • Metastases play a role in about 90% of cancer deaths

  • The purpose of this paper is to demonstrate, for any epithelial-mesenchymal transition (EMT) marker measured in primary tumor cancer cells from virtually any kind of cancer, how to use latent class analysis to estimate the sensitivity and specificity of the marker to assess detachment, and how to use risk reclassification to evaluate an outcomes prediction increment of the marker

  • When lymph node evaluation and radiologic imaging were the only predictors of all-cause mortality, the distribution of individual predicted probabilities ranged from 22% to 69%, with most subjects having the minimum probability of 22% (Table 3)

Read more

Summary

Introduction

Metastases play a role in about 90% of cancer deaths. Markers of epithelial-mesenchymal transition (EMT) measured in primary tumor cancer cells might provide diagnostic information about the likelihood that cancer cells have detached from the primary tumor. Physicians use two diagnostic tests jointly to assess detachment as part of tumor staging: examination of lymph nodes near the primary tumor and radiologic imaging. While highly useful, these methods do not always successfully detect metastases. An example of this imperfect accuracy is the fact that roughly 25% of colorectal cancer (CRC) patients diagnosed with local disease later are found to have a recurrence [2] Many of these recurrences could be due to metastases that were too small to be detected by imaging or lymph node evaluation at diagnosis. This could lead to more appropriate adjuvant chemotherapy decisions for patients who stand to benefit from it

Objectives
Methods
Results
Discussion
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call