Durable complete remission induced by cetuximab monotherapy in a patient infected with HIV and diagnosed with recurrent squamous cell carcinoma of the head and neck

Exceptional response to cetuximab monotherapy in a patient with metastatic oropharyngeal squamous cell carcinoma: a molecular insight

Background

Metastatic head and neck squamous cell carcinoma (HNSCC) carries a very poor prognosis. A better understanding of the molecular driver of the disease and the identification of biomarkers of response remain paramount for an effective personalized therapy.

Case report

We report an original case of a 56-year-old patient diagnosed with metastatic HNSCC to both kidneys, who experienced a long-lasting complete response to a single-agent cetuximab, a monoclonal antibody-targeting EGFR. Comprehensive multiplatform biomarker analysis of the tumor revealed the presence of phosphatidyl-inositol 3 kinase mutation, EGFR overexpression, and the absence of PD-1/PD-L1 expression. Since PI3K, a downstream effector of EGFR, is activated, the tumor regression may have occurred mainly through a cetuximab-induced immune-mediated response, rather than EGFR signal blockade. It is plausible that this effect was enhanced by the lack of PD-1 and PD-L1 expression.

Conclusion

Our case proposes that the absence of PD-1 and PD-L1 expression in conjunction with EGFR overexpression may correlate with better response to cetuximab in HNSCC. This hypothesis needs to be examined through a large clinical trial.

Is pathology necessary to predict mortality among men with prostate-cancer?

Background

Statistical models developed using administrative databases are powerful and inexpensive tools for predicting survival. Conversely, data abstraction from chart review is time-consuming and costly. Our aim was to determine the incremental value of pathological data obtained from chart abstraction in addition to information acquired from administrative databases in predicting all-cause and prostate cancer (PC)-specific mortality.

Methods

We identified a cohort of men with diabetes and PC utilizing population-based data from Ontario. We used the c-statistic and net-reclassification improvement (NRI) to compare two Cox- proportional hazard models to predict all-cause and PC-specific mortality. The first model consisted of covariates from administrative databases: age, co-morbidity, year of cohort entry, socioeconomic status and rural residence. The second model included Gleason grade and cancer volume in addition to all aforementioned variables.

Results

The cohort consisted of 4001 patients. The accuracy of the admin-data only model (c-statistic) to predict 5-year all-cause mortality was 0.7 (95% CI 0.69-0.71). For the extended model (including pathology information) it was 0.74 (95% CI 0.73-0.75). This corresponded to a change in category of predicted probability of survival among 14.8% in the NRI analysis.

The accuracy of the admin-data model to predict 5-year PC specific mortality was 0.76 (95% CI 0.74-0.78). The accuracy of the extended model was 0.85 (95% CI 0.83-0.87). Corresponding to a 28% change in the NRI analysis.

Conclusions

Pathology chart abstraction, improved the accuracy in predicting all-cause and PC-specific mortality. The benefit is smaller for all-cause mortality, and larger for PC-specific mortality.