Detección y evaluación del papel de la sarcopenia en ancianos con cáncer tratados con quimioterapia. Proyecto ONCOSARCO / Detection and evaluation of the role of sarcopenia in elderly patients with cancer treated with chemotherapy. ONCOSARCO project

Objetivos. Objetivos principales: elaborar un modelo predictor de toxicidad a la quimioterapia en ancianos oncológicos, a partir de variables relacionadas con la sarcopenia; identificar cuál de estos parámetros, sarcopenia o fragilidad, es el mejor predictor de toxicidad de la quimioterapia en ancianos. Material y métodos. Estudio prospectivo observacional, con pacientes ≥70 años tratados con quimioterapia en la Unidad de Cáncer en el Anciano de la Sección de Oncología Médica del Hospital Virgen de la Luz de Cuenca. Antes del inicio de la quimioterapia, a cada paciente se le determinará la fuerza muscular (handgrip, fuerza cilíndrica manual, fuerza de presión pulgar, flexión de cadera, extensión de rodilla), la masa muscular (índice de masa muscular esquelética) y la función física (velocidad 5 metros y test 5-Sit to stand). A lo largo de los 4 meses de tratamiento con quimioterapia, se recogerá la aparición de toxicidad severa. Se evaluará, mediante un primer análisis de regresión logística multinomial, cuál de ellos, sarcopenia (definición del European Working Group on Sarcopenia in Older People o fragilidad (criterios propuestos por Fried et al.), es el mejor predictor de toxicidad de la quimioterapia. Mediante un segundo análisis de regresión se pretende crear el primer modelo de predicción de toxicidad a la quimioterapia en el anciano oncológico, basado en la definición de sarcopenia. Conclusiones. Se espera que del análisis definitivo de este proyecto puedan encontrarse factores predictores de toxicidad a quimioterapia en ancianos oncológicos (AU)

Objectives. To develop a predictive model of toxicity to chemotherapy in elderly patients with cancer, using the variables associated with sarcopenia, and to identify which of these parameters, sarcopenia or frailty, is the best predictor of toxicity to chemotherapy in the elderly. Material and methods. A prospective observational study with patients ≥70 years treated with chemotherapy in the Cancer Unit for the Elderly, in the Medical Oncology Section of the Hospital Virgen de la Luz de Cuenca. The following tests will be performed by each patient before chemotherapy: muscle strength (handgrip, cylindrical handgrip, pinch gauge, hip flexion, knee extension), muscle mass (skeletal muscle mass index), and physical function (gait speed and 5STS test). The occurrence of severe toxicity will be recorded over a period of 4 months of chemotherapy treatment. It will be evaluated, using logistic regression analysis, whether sarcopenia (defined by the European Working Group on Sarcopenia in Older People) or frailty (defined by the phenotype of frailty) is the best predictor of chemotherapy toxicity. Using a multinomial logistic regression analysis, we will try to create the first model to predict toxicity to chemotherapy in elderly patients with diagnosis of cancer, based on the definition of sarcopenia. Conclusions. It is expected that the final analysis of this project will be useful to detect predictive factors of toxicity to chemotherapy in elderly patients with cancer (AU)

[Detection and evaluation of the role of sarcopenia in elderly patients with cancer treated with chemotherapy. ONCOSARCO project]. / Detección y evaluación del papel de la sarcopenia en ancianos con cáncer tratados con quimioterapia. Proyecto ONCOSARCO.

OBJECTIVES: To develop a predictive model of toxicity to chemotherapy in elderly patients with cancer, using the variables associated with sarcopenia, and to identify which of these parameters, sarcopenia or frailty, is the best predictor of toxicity to chemotherapy in the elderly. MATERIAL AND METHODS: A prospective observational study with patients ≥70 years treated with chemotherapy in the Cancer Unit for the Elderly, in the Medical Oncology Section of the Hospital Virgen de la Luz de Cuenca. The following tests will be performed by each patient before chemotherapy: muscle strength (handgrip, cylindrical handgrip, pinch gauge, hip flexion, knee extension), muscle mass (skeletal muscle mass index), and physical function (gait speed and 5STS test). The occurrence of severe toxicity will be recorded over a period of 4 months of chemotherapy treatment. It will be evaluated, using logistic regression analysis, whether sarcopenia (defined by the European Working Group on Sarcopenia in Older People) or frailty (defined by the phenotype of frailty) is the best predictor of chemotherapy toxicity. Using a multinomial logistic regression analysis, we will try to create the first model to predict toxicity to chemotherapy in elderly patients with diagnosis of cancer, based on the definition of sarcopenia. CONCLUSIONS: It is expected that the final analysis of this project will be useful to detect predictive factors of toxicity to chemotherapy in elderly patients with cancer.

Prognostic Role of Early and End-of-Neoadjuvant Treatment 18F-FDG PET/CT in Patients With Breast Cancer.

AIM: To determine the use of early and final treatment F-FDG PET/CT in the prediction of response to neoadjuvant chemotherapy (NAC) and its role in the prognosis of patients with locally advanced breast cancer (LABC). METHODS: One hundred thirty-two patients underwent a baseline FDG PET/CT (PET-1) after the second course of chemotherapy (PET-2) and after the last course (PET-3). Breast tumors were categorized into molecular phenotypes and risk categories according to the biological prognostic factors obtained by immunohistochemistry. PET/CT scans were semiquantitatively evaluated, obtaining the Δ% SUV1-2 and SUV1-3 in primary tumor and axillary lymph nodes to establish response groups attending to EORTC criteria. Moreover, a binary assessment was obtained classifying the studies as positive or negative. Histopathological response was obtained in breast and lymph node specimens. Overall survival (OS) and disease-free survival (DFS) were obtained after the follow-up. ROC analysis was performed to determine a cutoff value of Δ% SUV1-2 and SUV1-3 for the prediction of response and prognosis. Relations between phenotypes, metabolic behavior, final histopathological response, OS, and DFS were evaluated. RESULTS: In binary analysis, only PET-3 was able to predict histopathological response in lymph nodes. The cutoff values of %Δ SUV1-2 and %Δ SUV1-3 with the best sensitivity and specificity in the prediction of response in breast tumor were 62% (Se: 70% and Sp: 69%) and 84% (Se: 70% and Sp: 88%). A %ΔSUV1-3 of 74% in breast tumor was a predictor of DFS (AUC = 0.647; P = 0.037, Se: 52% and Sp: 66%). Kaplan-Meier analysis revealed significant relations between the binary lymph node assessment of PET-3 with OS (P = 0.016, χ = 5.78) and DFS (P = 0.003, χ = 9.10). CONCLUSIONS: End-of-treatment F-FDG PET/CT was a predictor of lymph node response and prognosis. Most of metabolic response variables related to histopathological response showed association with the prognosis.

Basal ¹8F-fluoro-2-deoxy-D-glucose positron emission tomography/computed tomography as a prognostic biomarker in patients with locally advanced breast cancer.

AIM: To explore the relationship between basal (18) F-FDG PET/CT information in breast tumours and survival in locally advanced breast cancer (LABC). METHODS: This prospective, multicentre study included 198 women diagnosed with LABC. All patients underwent (18) F-FDG PET/CT prior to treatment. The maximum standardized uptake value (SUVmax) in tumor (T), lymph nodes (N) and the N/T ratio was obtained in all cases. Stage according to PET/CT imaging (metabolic stage) and conventional imaging techniques (clinical stage) was established. During follow-up, patient status was established (disease free status or not). The relationship between all the variables and overall survival (OS) and disease-free survival (DFS) was analysed using the Kaplan-Meier and Cox regression methods. A ROC analysis was performed to obtain a cut-off value of SUVmax that was useful in the prediction of outcome. RESULTS: The mean SUVmax ± SD values in the primary tumour, lymph nodes and the SUVmax N/T index were 7.40 ± 5.57, 4.17 ± 4.74 and 0.73 ± 1.20, respectively. Higher semiquantitative metabolic values were found in more advanced metabolic and clinical stages. During follow-up, 78.4 % of patients were free of disease. Significant relationships were observed between SUVT and SUVN and patient status. With respect to OS and DFS, significant differences were detected for the metabolic stage. Kaplan-Meier analysis revealed that using the cut-off values, a primary-tumour SUVmax ≥ 6.05 or a nodal SUVmax ≥2.25 were significantly correlated with DFS and OS. CONCLUSION: PET imaging with (18) F-FDG offers prognostic information for LABC that can be obtained preoperatively and noninvasively.

Glycolytic activity with 18F-FDG PET/CT predicts final neoadjuvant chemotherapy response in breast cancer.

The purpose of the present study is to explore the relation between glycolytic metabolism assessed by (18)F-fluoro-2-deoxy-D-glucose positron emission tomography/computed tomography ((18)F-FDG PET/CT) and final neoadjuvant chemotherapy (NC) response in locally advanced breast tumors. Of women with breast cancer, 126 were prospectively evaluated. All patients underwent (18)F-FDG PET/CT previous to NC. Standard uptake value (SUV) max was calculated in the primary tumor. After NC, residual primary tumor specimen was histopathologically classified according to Miller and Payne tumor regression grades (TRG), from G1 to G5 and in response groups as good responders (G4 or G5), partial responders (G2 or G3), and non-responders (G1). Furthermore, residual lesions were classified following a binary assessment as responders (G4 or G5) and non-responders (the rest of cases). The relationship between SUV max with TRG and response groups was evaluated. Of tumors, 127 were assessed (a patient had bilateral breast lesions). TRG were as follows: G1 (27), G2 (27), G3 (32), G4 (11), and G5 (30). Forty-one were classified as good responders, 59 as partial responders, and 27 as non-responders. For the binary assessment, 41 lesions were classified as responders and 86 as non-responders. We found statistical differences (p=0.02) between the mean SUV max and TRG with greater SUV values for G5 compared to the other TRG. Good responders showed greater mean SUV max ± SD compared to partial responders and non-responders (10.51 ± 6.64 for good responders, 6.94 ± 5.81 for partial responders, and 5.23 ± 2.76 for non-responders; p=0.001). Baseline tumor metabolism assessing by FDG PET/CT was associated with the final histopathologic status after neoadjuvant chemotherapy, with greater SUV max values for good responders compared to the less responder cancers.

Early and delayed prediction of axillary lymph node neoadjuvant response by (18)F-FDG PET/CT in patients with locally advanced breast cancer.

PURPOSE: To determine the utility of (18)F-FDG (FDG) PET/CT performed in an early and delayed phase during neoadjuvant chemotherapy in the prediction of lymph node histopathological response in patients with locally advanced breast cancer. METHODS: FDG PET/CT studies performed in 76 patients (mean age 53 years) at baseline (PET-1), after the second course of chemotherapy (PET-2) and after the last course of chemotherapy (PET-3) were prospectively analysed. Inclusion criteria were lymph node involvement detected by PET/CT and non-sentinel node biopsy before or after the baseline PET/CT scan. Following the recommendations of the 12th International Breast Conference (St. Gallen), the patients were divided into five subgroups in relation to biological prognostic factors by immunohistochemistry. For diagnosis visual and semiquantitative analyses was performed. Absence of detectable lymph node uptake on the PET-2 or PET-3 scan with respect to the PET-1 scan was considered metabolic complete response (mCR). Lymph nodes were histopathologically classified according the lymph node regression grade and in response groups as pathological complete response (pCR) or not pCR (type A/D or B/C of the Smith grading system, respectively). ROC analysis was performed to determine a cut-off value of Δ% SUV1-2 and SUV1-3 for prediction of nodal status after chemotherapy. An association between mCR and pCR was found (Cohen's kappa analysis), and associations between phenotypes and metabolic behaviour and the final histopathological status were also found. RESULTS: Lymph node pCR was seen in 34 patients. The sensitivity, specificity, and positive and negative predictive values of PET-2 and PET-3 in establishing the final status of the axilla after chemotherapy were 52 %, 45 %, 50 % and 47 %, and 33 %, 84 %, 67 % and 56 %, respectively. No significant relationship was observed between mCR on PET-2 and PET-3 and pCR (p = 0.31 and 0.99, respectively). Lymph node metabolism on PET-1 was not able to predict the final histopathological status, whereas basal carcinomas showed a higher rate of pCR (70.6 %) than the other groups (p = 0.03). CONCLUSION: FDG PET/CT seems to have limitations in both the early and delayed evaluation of lymph node status after chemotherapy, with reduced predictive values.

Molecular subtypes of breast cancer: metabolic correlation with ¹8F-FDG PET/CT.

PURPOSE: To determine whether the metabolic features of breast tumours differ among molecular subtypes. METHODS: This prospective study included 168 women diagnosed with locally advanced breast cancer. PET/CT was requested in the initial staging before neoadjuvant treatment (multicentre study, FISCAM grant). All patients underwent an ¹8F-FDG PET/CT scan with a dual time-point acquisition. Both examinations (PET-1 and PET-2) were evaluated qualitatively and semiquantitatively with calculation of SUVmax (SUV-1 and SUV-2, respectively), and the percentage variation in the SUVs and retention indexes (RI) between PET-1 and PET-2 in the breast tumour were calculated. Biological prognostic parameters, including the steroid receptor status, HER-2 expression, proliferation rate (Ki-67) and grading, were determined from primary tumour tissue. Tumour subtypes were classified following the recommendations of the 12th International Breast Conference, by immunohistochemical surrogates as luminal A, luminal B-HER2(-), luminal B-HER2(+), HER2(+) or basal. Metabolic semiquantitative parameters and molecular subtypes were correlated. RESULTS: Of the 168 tumours, 151 were classified: 16 were luminal A, 53 were luminal B-HER2(-), 29 were luminal B-HER2(+), 18 were HER2(+) and 35 were basal. There were significant differences between SUV-1 and SUV-2 and the different subtypes, with higher SUVs in HER2(+) and basal tumours. No significant differences were found with respect to RI. CONCLUSION: Semiquantitative metabolic parameters showed statistically significant differences among the molecular subtypes of the tumours evaluated. Therefore, there seems to be a relationship between molecular and glycolytic phenotypes.

Semi-quantitative lymph node assessment of (18)F-FDG PET/CT in locally advanced breast cancer: correlation with biological prognostic factors.

PURPOSE: The aim of this study was to analyse the correlation between dual-time-point (18)F-2-deoxy-2-fluoro-D-glucose (FDG) uptakes in lymph nodes assessed by positron emission tomography (PET)/CT and histopathological and immunohistochemical prognostic factors. METHODS: Seventy-five women with locally advanced breast cancer were prospectively evaluated. PET/CT was requested in the initial staging previous to adjuvant chemotherapy (multicentre study). All of the patients underwent (18)F-FDG PET/CT with a dual-time-point acquisition. Both examinations were evaluated qualitatively and semi-quantitatively with calculation of maximum standardized uptake values (SUV(max)) in PET-1 (SUV-1) and in PET-2 (SUV-2) and the percentage variation of the SUV or retention index (RI) between PET-1 and PET-2 in lymph nodes with the greater (18)F-FDG uptake. The biological prognostic parameters such as the steroid receptor status, p53 and HER2 expression, proliferation rate (Ki-67) and grading were determined from tissue of the primary tumour. Metabolic and biological parameters were correlated using Spearman's rank-order correlation coefficient and Mann-Whitney U and Kruskal-Wallis tests. RESULTS: Negative receptor status was correlated with higher SUV-1, SUV-2 and RI in lymph nodes. The results were significant for progesterone receptor status. p53 over-expression and triple-negative status were associated with greater semi-quantitative parameters in lymph nodes. Higher tumoural grades were related with greater semi-quantitative parameters (p > 0.05). CONCLUSION: Biological factors of bad prognosis were correlated with higher semi-quantitative metabolic values in lymph nodes. Therefore these results appear to reveal biological significance of lymph node (18)F-FDG accumulation.