[Colorectal cancer and preoperative geriatric assessment]

With the ageing of the population and the increase in the incidence of cancer in the population over 75 years of age, a partnership between geriatricians and oncologists is becoming necessary to optimise the management of these patients. There is great variability in the profiles of elderly patients and age cannot be the only criterion of the decision making. Thus, it is necessary to identify patients who will benefit from an in-depth geriatric assessment (IGA) and the G8 screening tool used in oncology consultations allows to do so. The EGA offers a multidisciplinary approach to functional, psychological, nutritional, cognitive and social status of the person, and has been shown to have prognostic value for survival and relevance in guiding treatment choices.

A Risk Stratification Model for Predicting Overall Survival and Surgical Benefit in Triple-Negative Breast Cancer Patients With de novo Distant Metastasis

Background and Aims: This research aimed to construct a novel model for predicting overall survival (OS) and surgical benefit in triple-negative breast cancer (TNBC) patients with de novo distant metastasis. Methods: We collected data from the Surveillance, Epidemiology, and End Results (SEER) database for TNBC patients with distant metastasis between 2010 and 2016. Patients were excluded if the data regarding metastatic status, follow-up time, or clinicopathological information were incomplete. Univariate and multivariate analyses were applied to identify significant prognostic parameters. By integrating these variables, a predictive nomogram and risk stratification model were constructed and assessed with C-indexes and calibration curves. Results: A total of 1,737 patients were finally identified. Patients enrolled from 2010 to 2014 were randomly assigned to two cohorts, 918 patients in the training cohort and 306 patients in the validation cohort I, and 513 patients enrolled from 2015 to 2016 were assigned to validation cohort II. Seven clinicopathological factors were included as prognostic variables in the nomogram: age, marital status, T stage, bone metastasis, brain metastasis, liver metastasis, and lung metastasis. The C-indexes were 0.72 [95% confidence interval [CI] 0.68-0.76] in the training cohort, 0.71 (95% CI 0.68-0.74) in validation cohort I and 0.71 (95% CI 0.67-0.75) in validation cohort II. Calibration plots indicated that the nomogram-based predictive outcome had good consistency with the recoded prognosis. A risk stratification model was further generated to accurately differentiate patients into three prognostic groups. In all cohorts, the median overall survival time in the low-, intermediate- and high-risk groups was 17.0 months (95% CI 15.6-18.4), 11.0 months (95% CI 10.0-12.0), and 6.0 months (95% CI 4.7-7.3), respectively. Locoregional surgery improved prognosis in both the low-risk [hazard ratio [HR] 0.49, 95% CI 0.41-0.60, P < 0.0001] and intermediate-risk groups (HR 0.55, 95% CI 0.46-0.67, P < 0.0001), but not in high-risk group (HR 0.73, 95% CI 0.52-1.03, P = 0.068). All stratified groups could prognostically benefit from chemotherapy (low-risk group: HR 0.50, 95% CI 0.35-0.69, P < 0.0001; intermediate-risk group: HR 0.34, 95% CI 0.26-0.44, P < 0.0001; and high-risk group: HR 0.16, 95% CI 0.10-0.25, P < 0.0001). Conclusion: A predictive nomogram and risk stratification model were constructed to assess prognosis in TNBC patients with de novo distant metastasis; these methods may provide additional introspection, integration and improvement for therapeutic decisions and further studies.

The Crossroads of Precision Medicine and Therapeutic Decision-Making: Use of an Analytical Computational Platform to Predict Response to Cancer Treatments

Metastatic cancer is a medical challenge that has been historically resistant to treatments. One area of leverage in cancer care is the development of molecularly-driven combination therapies, offering the possibility to overcome resistance. The selection of optimized treatments based on the complex molecular features of a patient’s tumor may be rendered easier by using a computer-assisted program. We used the PreciGENE^® platform that uses multi-pathway molecular analysis to identify personalized therapeutic options. These options are ranked using a predictive score reflecting the degree to which a therapy or combination of therapies matches the patient’s biomarker profile. We searched PubMed from February 2010 to June 2017 for all patients described as exceptional responders who also had molecular data available. Altogether, 70 patients with cancer who had received 202 different treatment lines and who had responded (stable disease ≥12 months/partial or complete remission) to ≥1 regimen were curated. We demonstrate that an algorithm reflecting the degree to which patients were matched to the drugs administered correctly ranked the response to the regimens with a sensitivity of 84% and a specificity of 77%. The difference in matching score between successful and unsuccessful treatment lines was significant (median, 65% versus 0%, p-value <0.0001).

Will the presence of the patient at multidisciplinary meetings influence the decision in head and neck oncology management?

OBJECTIVES

Multidisciplinary team meetings (MTM) are essential in the choice of a therapeutic strategy in head and neck cancer. In many centres patients attend MTMs and are examined by the team. The aim of this study was to assess the influence of the patient's presence on therapeutic decisions.

STUDY DESIGN

Prospective study of 119 consecutive patients.

METHODS

Two therapeutic situations were compared: the therapeutic decision taken following discussion of the patient's file in the MTM (D1) and the therapeutic decision taken after examination of the patient during MTMs (D2). Concordance between the two situations was measured.

RESULTS

Concordance between D1 and D2 was 97%. No factors likely to decrease concordance were identified. Decisions taken during MTMs were acted upon for 97% of the patients.

CONCLUSION

The presence of the patient during MTMs is not essential if the files are thoroughly presented and discussed.