Algorithms of follow-up in patients with head and neck cancer in relation to primary location and advancement. Consensus of Polish ENT Society Board and Head Neck Experts

Summary

The algorithm of follow-up in patients with head and neck cancer (HNC) has been prepared by a board of Polish Head Neck and Oncology Experts. The aim of this research is to focus on the specificity of HNC monitoring, to review the current trends in follow-up, and to adapt the evidence-based medicine international standards to the capabilities of the local healthcare service.

Materials and methods

The first methodological step was to categorize HNCs according to the estimated risk of failure after the adequate first-line treatment and according to the possibility of effective salvage treatment, resulting in improved overall survival. The final method used in this work was to prepare an authors' original monitoring algorithm for HNC groups with a high, moderate, and low risk of recurrence in combination with a high or low probability of using an effective salvage.

Results

Four categories were established: Ia. low risk of recurrence + effective organ preservation feasible; Ib. low risk of recurrence + effective salvage feasible; II. moderate risk of recurrence + effective salvage feasible; III. high risk of recurrence + effective salvage feasible; and IV. high risk of recurrence + no effective salvage feasible. Follow-up visit consisting of 1. ENT examination + neck ultrasound, 2. imaging HN tests, 3. chest imaging, 4. blood tests, and 5. rehabilitation (speech and swallowing) was scheduled with a very different frequency, at the proposed monthly intervals, tailored to the needs of the group. The number of visits for individual groups varies from 1 to 8 in the first 2 years and from 1 to 17 in the entire 5-year monitoring period. Group IV has not been included in regular follow-up, visits on own initiative of the patient if symptomatic, or supportive care needs, having in mind that third-line therapy and immune checkpoint inhibitors are available.

Conclusion

Universal monitoring algorithm for HNC four groups with a high, moderate, and low risk of recurrence after the adequate treatment in combination with a high or low probability of using an effective salvage is an innovative approach to redeploying system resources and ensuring maximum benefit for patients with HNC.

A Statistical Approach to Determine the Optimal Duration of Post-Treatment Follow-Up: Application to Metastatic Nonseminomatous Germ Cell Tumors

BACKGROUND

The objective of this study was to present a statistical method to define an optimal duration of follow-up for patients in remission after treatment for cancer, for detection of recurrences.

PATIENTS AND METHODS

Surveillance duration was estimated using the 2-step approach proposed by Mould et al. Relapse-free interval was modeled using the parametric cure model proposed by Boag. The optimal length of follow-up was then estimated as the minimal elapsed time after which the probability of a patient to relapse and to be cured with success is below a given threshold value. The method is applied to 2 real data sets of patients treated for metastatic non seminomatous germ-cell tumors: T93BP and T93MP.

RESULTS

For the T93BP, cure rate was estimated at 91.3% and proportions of patients who relapsed after 3 and 5 years were estimated at 0.5% and 0.2%. With a probability of success of salvage treatment equal to 80% and 50%, numbers of delayed cases after 5 years were 2 and 1. For T93MP, the proportion of patients who presented relapse after 5 and 10 years were estimated at 5.2% and 2.6%. Considering a probability of salvage treatment equal to 20%, the number of delayed cases after 5 and 10 years were 10 and 5.

CONCLUSION

Using this methodology, duration of post-therapeutic follow-up might be tailored according to an objective criteria: the number of patients who present relapse after the end of follow-up and who could have been treated with success in case of early detection.

Prediction of long-term cumulative incidences based on short-term parametric model for competing risks: application in early breast cancer

Use of parametric statistical models can be a solution to reduce the follow-up period time required to estimate long-term survival. Mould and Boag were the first to use the lognormal model. Competing risks methodology seems more suitable when a particular event type is of interest than classical survival analysis. The objective was to evaluate the ability of the Jeong and Fine model to predict long-term cumulative incidence. Survival data recorded by Institut Curie (Paris) from 4761 breast cancer patients treated and followed between 1981 and 2013 were used. Long-term cumulative incidence rates predicted by the model using short-term follow-up data were compared to non-parametric estimation using complete follow-up data. 20- or 25-year cumulative incidence rates for loco-regional recurrence and distant metastasis predicted by the model using a maximum of 10 years of follow-up data had a maximum difference of around 6 % compared to non-parametric estimation. Prediction rates were underestimated for the third and composite event (contralateral or second cancer or death). Predictive ability of Jeong and Fine model on breast cancer data was generally good considering the short follow-up period time used for the estimation especially when a proportion of patient did not experience loco-regional recurrence or distant metastasis.