Thyroid cancer surgery guidelines in an era of de-escalation

Well-differentiated thyroid carcinoma has seen a tremendous rise in global incidence over the past three decades, largely owing to widespread screening and identification of small, incidentally detected tumors. With this increased incidence has emerged a movement questioning whether all cases of thyroid cancer merit a treatment approach focused on oncologic completeness. Such trends towards thoughtful, evidence-based treatment de-escalation paradigms reflect better risk stratification of thyroid cancers, and recognition that not all detected disease poses a threat to health or survival. Thus, national and professional guidelines are evolving to incorporate higher thresholds for surgery, acceptance of less than total thyroidectomy in specific circumstances, higher thresholds for adjuvant therapy, and introduction of the role of active surveillance for selected cases of low risk disease. Despite these common themes, there are significant differences among guidelines. This lack of consensus in guidelines persists due to variation in clinical practice patterns, differences in consideration and interpretation of existing evidence, cultural and geographical considerations, and resources available for both diagnosis and treatment.

Abstract 20: Individualized outcome prognostication for patients with larynx cancer

Background: Accurate and individualized prognostication is obligatory to the optimal management of larynx cancer. The wide variety of treatment options has made decision making complex and challenging for patients and physicians. Predictive models have been developed to calculate the risk of oncologic outcomes using individualized patient data. Implementing these predictive models into clinical practice may improve patient counseling and clinical management, but preemptive validation of their accuracy and reliability is essential.

Aim: To utilize an independent patient cohort to characterize and externally validate existing prognostic calculators for larynx cancer.

Methods: Four published prognostic calculators that use individualized information to predict 5-year overall survival for patients with larynx cancer were utilized. Analyses were performed using an independent cohort of 246 patients with previously untreated larynx cancer diagnosed between 2002 and 2012. Clinical and oncologic factors were extracted from a prospective epidemiology database and confirmed via chart abstraction. Survival estimates were calculated using each of the four models and subsequent analyses compared the calculators to one another and in reference to observed outcomes. Median follow-up was 48 months.

Results: The observed mean 5-year overall survival within the entire cohort was 72%, whereas each of the calculators predicted significantly worse outcomes, with a mean 5-year overall survival of 47%. One model predicted notably lower survival estimates compared to the others, particularly when assigning outcomes to patients with higher risk disease; otherwise, correlation coefficients were fair (0.62-0.81). Analyses of discrimination suggested that two calculators underperform in their capacity to stratify low- and high-risk patients, whereas two others underperform in their discrimination of mid-stage risk. The AUC ranged from 0.65 to 0.73. C-index values were similar for each of the four models (0.66 to 0.69). Multivariate modeling for calculator-estimated survival estimates identified surgical intervention and induction chemotherapy as predictive of better-than-expected outcomes.

Conclusion: Prognostic calculators varied in their ability to accurately predict survival in an external cohort of patients with larynx cancer. Suboptimal reliability and accuracy limit the potential integration of existing individualized prediction tools into routine clinical decision-making. The calculators significantly underestimated survival among patients treated with induction chemotherapy and primary surgery, suggesting that treatment modality may need to be better integrated into revised prediction tools. Deficiencies in calculator performance may be further explained by institutional variation in oncologic outcomes.

Citation Format: Connor W. Hoban, Emily L. Belille, Lauren Beesley, Gregory T. Wolf, Jeremy M.G. Taylor, Andrew G. Shuman. Individualized outcome prognostication for patients with larynx cancer [abstract]. In: Proceedings of the AACR-AHNS Head and Neck Cancer Conference: Optimizing Survival and Quality of Life through Basic, Clinical, and Translational Research; April 23-25, 2017; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2017;23(23_Suppl):Abstract nr 20.

Individualized outcome prognostication for patients with laryngeal cancer

BACKGROUND

Accurate prognostication is essential to the optimal management of laryngeal cancer. Predictive models have been developed to calculate the risk of oncologic outcomes, but extensive external validation of accuracy and reliability is necessary before implementing them into clinical practice.

METHOD

Four published prognostic calculators that predict 5-year overall survival for patients with laryngeal cancer were evaluated using patient information from a prospective epidemiology study cohort (n = 246; median follow-up, 60 months) with previously untreated, stage I through IVb laryngeal squamous cell carcinoma.

RESULTS

Different calculators yielded substantially different predictions for individual patients. The observed 5-year overall survival was significantly higher than the averaged predicted 5-year overall survival of the 4 calculators (71.9%; 95% confidence interval [CI], 65%-78%] vs 47.7%). Statistical analyses demonstrated the calculators' limited capacity to discriminate outcomes for risk-stratified patients. The area under the receiver operating characteristic curve ranged from 0.68 to 0.72. C-index values were similar for each of the 4 models (range, 0.66-0.68). There was a lower than expected hazard of death for patients who received induction (bioselective) chemotherapy (hazard ratio, 0.46; 95% CI, 0.24-0.88; P = .024) or primary surgical intervention (hazard ratio, 0.43; 95 % CI, 0.21-0.90; P = .024) compared with those who received concurrent chemoradiation.

CONCLUSIONS

Suboptimal reliability and accuracy limit the integration of existing individualized prediction tools into routine clinical decision making. The calculators predicted significantly worse than observed survival among patients who received induction chemotherapy and primary surgery, suggesting a need for updated consideration of modern treatment modalities. Further development of individualized prognostic calculators may improve risk prediction, treatment planning, and counseling for patients with laryngeal cancer. Cancer 2018;124:706-16. © 2017 American Cancer Society.

Individualized risk prediction of outcomes for oral cavity cancer patients

BACKGROUND

Optimal management of oral cancer relies upon accurate and individualized risk prediction of relevant clinical outcomes. Individualized prognostic calculators have been developed to guide patient-physician communication and treatment-related decision-making. However it is critical to scrutinize their accuracy prior to integrating into clinical care.

AIM

To compare and evaluate oral cavity cancer prognostic calculators using an independent dataset.

METHODS

Five prognostic calculators incorporating patient and tumor characteristics were identified that evaluated five-year overall survival. A total of 505 patients with previously untreated oral cancer diagnosed between 2003 and 2014 were analyzed. Calculators were applied to each patient to generate individual predicted survival probabilities. Predictions were compared among prognostic tools and with observed outcomes using Kaplan-Meier plots, ROC curves and calibration plots.

RESULTS

Correlation between the five calculators varied from 0.59 to 0.86. There were considerable differences between individual predictions from pairs of calculators, with as many as 64% of patients having predictions that differed by more than 10%. Four of five calculators were well calibrated. For all calculators the predictions were associated with survival outcomes. The area under the ROC curve ranged from 0.65 to 0.71, with C-indices ranging from 0.63 to 0.67. An average of the 5 predictions had slightly better performance than any individual calculator.

CONCLUSION

Five prognostic calculators designed to predict individual outcomes of oral cancer differed significantly in their assessments of risk. Most were well calibrated and had modest discriminatory ability. Given the increasing importance of individualized risk prediction, more robust models are needed.