Role of Positron Emission Tomography in the Treatment of Occult Disease in Head-and-Neck Cancer: A Modeling Approach

Abstract

Purpose To determine under what conditions PET imaging will be useful in decisions regarding the use of radiation therapy for the treatment of clinically-occult lymph node metastases in head and neck cancer. Methods and Materials A decision model of PET imaging and its downstream effects on radiation therapy outcomes was constructed using an influence diagram. This model included the sensitivity and specificity of PET as well as the type and stage of the primary tumor. These parameters were varied to determine the optimal strategy for imaging and therapy for different clinical situations. Maximum Expected Utility was the metric by which different actions were ranked. Results For primary tumors with a low probability of lymph node metastases, the sensitivity of PET should be maximized and 50 Gy should be delivered if PET is positive and 0 Gy if negative. As the probability for lymph node metastases increases, PET imaging becomes unnecessary in some situation and the optimal dose to the lymph nodes increases. The model needed to include the causes of certain health states in order to predict current clinical practice. Conclusion The model demonstrated the ability to reproduce expected outcomes for a range of tumors and provided recommendations for different clinical situations. The differences between the optimal policies and current clinical practice is likely due to a disparity between stated clinical decision processes and actual decision making by clinicians.

Is elective neck dissection necessary in cases of laryngeal recurrence after previous radiotherapy for early glottic cancer?

“…Positron emission tomography has a low specificity and sensitivity for nodal metastases of diameter less than 6 mm. 13,14 Recently, CT perfusion scans have been shown to depict nodal metastases of less than 1 cm in diameter. 15 In untreated patients, cervical lymphatic tumour spread follows a predictable path; 10 this knowledge has led to improvements in the surgical management of clinically staged N 0 laryngeal cancer.…”

Decision analytic modeling for the economic analysis of proton radiotherapy for non-small cell lung cancer

“…We find that the AUC alone is not sufficient to determine the clinical usefulness of a test. This is primarily due to the fact that maximizing the area under the ROC places equal weights on false-positive and false-negative results (44,45). By providing the opportunity to model the trade-offs between sensitivity and specificity, the influence diagram was shown to be instrumental in expanding the possibilities for exploring different scenarios.…”

Machine learning and modeling: Data, validation, communication challenges

“…However, it assumes that specificity and sensitivity are of equal importance to the decision-maker, which may not always be the case for physicians or physicists working in the clinic. [47][48][49][50] Furthermore, ascribing unwarranted clinical significance sometimes to results based on marginal AUC values (e.g., <0.7), does occur often and should be cautiously addressed in scientific publications and presentations. 51,52 ML provides a model approximation of reality (correlations), to make clinically relevant predictions with associated error characteristics.…”

“…For example, standard maximization of the area under a receiver operating characteristic curve (AUC) is a convenient and easy‐to‐comprehend metric. However, it assumes that specificity and sensitivity are of equal importance to the decision‐maker, which may not always be the case for physicians or physicists working in the clinic . Furthermore, ascribing unwarranted clinical significance sometimes to results based on marginal AUC values (e.g., <0.7), does occur often and should be cautiously addressed in scientific publications and presentations .…”