Genomically matched therapy in refractory colorectal cancer according to ESMO Scale for Clinical Actionability of Molecular Targets: experience of a comprehensive cancer centre network.

Efficiency of expanded genomic profiling (EGP) programmes in terms of final inclusion of patients in genomically matched therapies is still unknown. Fit patients with advanced and refractory colorectal cancer (CRC) were selected for an EGP programme. Next-generation sequencing (NGS) analysis from formalin-fixed paraffin-embedded tumour samples was performed. The purpose was to describe the prevalence of genomic alterations defined by the ESMO Scale for Clinical Actionability of Molecular Targets (ESCAT), as well as the percentage of patients finally included in genomically guided clinical trials. In total, 187 patients were recruited. Mutational profile was obtained in 177 patients (10 patients were failure due to insufficient tumour sample), copy number alterations in 41 patients and fusions in 31 patients. ESCAT-defined alterations were detected in 28.8% of the intention-to-analyse population. BRAF V600E was clustered in ESCAT I, with a prevalence of 3.7%, KRAS G12C and ERBB2 amplification were clustered in ESCAT II, whose prevalence was 4.2% and 1.6%, respectively. Most alterations were classified in ESCAT III (mutations in ERBB2, PIK3CA or FGFR genes and MET amplification) and IV (mutations in BRAF non-V600E, ERBB3, FBXW7, NOTCH, RNF43), with a single prevalence under 5%, except for PIK3CA mutation (9%). The final rate of inclusion into genomically guided clinical trials was 2.7%, including therapies targeting BRAF V600E or RNF43 mutations in two patients each, and ERBB2 mutation in one patient. In conclusion, EGP programmes in patients with advanced CRC are feasible and identify a subset of patients with potentially druggable genomic alterations. However, further efforts must be made to increase the rate of patients treated with genomically guided therapies.

Development and Validation of an Early Mortality Risk Score for Older Patients Treated with Chemotherapy for Cancer.

Background: Estimation of life expectancy in older patients is relevant to select the best treatment strategy. We aimed to develop and validate a score to predict early mortality in older patients with cancer. Patients and Methods: A total of 749 patients over 70 years starting new chemotherapy regimens were prospectively included. A prechemotherapy assessment that included sociodemographic variables, tumor/treatment variables, and geriatric assessment variables was performed. Association between these factors and early death was examined using multivariable logistic regression. Score points were assigned to each risk factor. External validation was performed on an independent cohort. Results: In the training cohort, the independent predictors of 6-month mortality were metastatic stage (OR 4.8, 95% CI [2.4-9.6]), ECOG-PS 2 (OR 2.3, 95% CI [1.1-5.2]), ADL ≤ 5 (OR 1.7, 95% CI [1.1-3.5]), serum albumin levels ≤ 3.5 g/dL (OR 3.4, 95% CI [1.7-6.6]), BMI < 23 kg/m2 (OR 2.5, 95% CI [1.3-4.9]), and hemoglobin levels < 11 g/dL (OR 2.4, 95% CI (1.2-4.7)). With these results, we built a prognostic score. The area under the ROC curve was 0.78 (95% CI, 0.73 to 0.84), and in the validation set, it was 0.73 (95% CI: 0.67-0.79). Conclusions: This simple and highly accurate tool can help physicians making decisions in elderly patients with cancer who are planned to initiate chemotherapy treatment.

Prediction of Chemotoxicity, Unplanned Hospitalizations and Early Death in Older Patients with Colorectal Cancer Treated with Chemotherapy.

PURPOSE: To identify risk factors for toxicity, unplanned hospitalization (UH) and early death (ED) in older patients with colorectal carcinoma (CRC) initiating chemotherapy. METHODS: 215 patients over 70 years were prospectively included. Geriatric assessment was performed before treatment, and tumor and treatment variables were collected. The association between these factors and grade 3-5 toxicity, UH and ED (<6 months) was examined by using multivariable logistic regression. Score points were assigned to each risk factor. RESULTS: During the first 6 months of treatment, 33% of patients developed grade 3-5 toxicity, 31% had UH and 23% died. Risk factors were, for toxicity, instrumental activities of daily living, creatinine clearance, weight loss and MAX2 index; for UH, Charlson Comorbidity Score, creatinine clearance, weight loss, serum albumin, and metastatic disease; and for ED, basic activities in daily living, weight loss, metastatic disease, and hemoglobin levels. Predictive scores were built with these variables. The areas under receiver operation characteristic (ROC) curves for toxicity, UH and ED were 0.70 (95% CI: 0.64-0.766), 0.726 (95% IC: 0.661-0.799) and 0.74 (95% IC: 0.678-0.809), respectively. CONCLUSION: Simple scores based on geriatric, tumor and laboratory characteristics predict severe toxicity, UH and ED, and may help in treatment planning.

Undertreatment and overtreatment in older patients treated with chemotherapy.

BACKGROUND: Inconsistent doses and schemes are commonly used in older patients receiving cancer chemotherapy. We performed this study in patients with cancer and age ≥ 70 years to determine the frequency of undertreatment and overtreatment as well as factors influencing the decision to modify chemotherapy doses. PATIENTS AND METHODS: Patients aged ≥70 years starting new chemotherapy regimens were prospectively included in a multicentre study. The schedule and drug doses were determined by the treating oncologist. Pre-chemotherapy assessment included sociodemographics, treatment details and geriatric assessment (GA) variables. Association between these factors and undertreatment (use of less intensive cancer treatment [LICT] in a fit patient) or overtreatment (use of standard cancer treatment in an unfit older patient) were examined by multivariate logistic regression. RESULTS: Three- hundred ninety-seven patients were included, 43% of whom received LICT. If not adjusted for GA, toxicity did not differ between those receiving LICT (38%) or standard doses of chemotherapy (37%). If the dose of chemotherapy was analyzed according to the results of GA 61 (15%) patients had been undertreated and 133 (34%) had been overtreated. Undertreatment was related with increasing age and decreased renal function. Factors related with overtreatment were younger age, curative intention of treatment, prescription of G-CSF as primary prophylaxis and adequate cognitive status. Overtreated patients had more grade 3-4 toxicity than those receiving treatment adapted to fragility (42% vs 31%; p < 0.05). CONCLUSIONS: The use of chemotherapy without considering GA leads to overtreatment more commonly than undertreatment in older patients with cancer. Oncologists should take into account the results of GA to stratify patients and to avoid under or overtreatment.

Predicting Chemotherapy Toxicity in Older Patients with Cancer: A Multicenter Prospective Study.

BACKGROUND: Standard oncology tools are inadequate to distinguish which older patients are at higher risk of developing chemotherapy-related complications. MATERIALS AND METHODS: Patients over 70 years of age starting new chemotherapy regimens were prospectively included in a multicenter study. A prechemotherapy assessment that included sociodemographics, tumor/treatment variables, and geriatric assessment variables was performed. Association between these factors and the development of grade 3-5 toxicity was examined by using logistic regression. RESULTS: A total of 551 patients were accrued. Chemotherapy doses (odds ratio [OR] 1.834; 95% confidence interval [CI] 1.237-2.719) and creatinine clearance (OR 0.989; 95% CI 0.981-0.997) were the only factors independently associated with toxicity. Only 19% of patients who received reduced doses of chemotherapy and had a creatinine clearance ≥40 mL/minute had grade 3-4 toxicity, compared with 38% of those who received standard doses or had a creatinine clearance <40 mL/minute (p < .0001). However, no satisfactory multivariate model was obtained using different selection approaches. CONCLUSION: Chemotherapy doses and renal function were identified as the major risk factors for developing severe toxicity in the older patient. These factors should be considered when planning to initiate a new chemotherapy regimen and should also lead to a closer follow-up in these patients. IMPLICATIONS FOR PRACTICE: Older patients are more vulnerable to chemotherapy toxicity. However, standard tools are inadequate to identify who is at higher risk of developing chemotherapy-related complications. Chemotherapy doses (standard vs. reduced) and renal function were identified as the major risk factors for developing severe toxicity in the elderly. These factors should be considered when planning to initiate a new chemotherapy regimen and should also lead to a closer follow-up.