Cardiac telerehabilitation with long-term follow-up reduces GlycA and improves lipoprotein particle profile: A randomised controlled trial.

BACKGROUND: A 10-month strategy of cardiac telerehabilitation (CTR) improved outcomes over a standard centre-based cardiac rehabilitation (CBCR), as recently published. We hypothesised that prolonged telerehabilitation could also improve proinflammatory status and lipoprotein particle composition. METHODS: A randomised controlled trial compared a prolonged CTR program with CBCR in post-ACS patients. Patient's age was 18-72 years with low-risk criteria. Blood samples were drawn at baseline, at 4- and 10-months follow-up. Advanced lipoprotein characterization was performed using the NMR-based Liposcale test. Signals from glycoproteins (GlycA and GlycB) were also assessed. RESULTS: The final analysis included 31 patients in the CTR group and 25 patients in the CBCR group. GlycA decreased in the CTR group (p = 0,007). LDL particle number (LDL-P) increase in both groups, but it was at the expense of small-sized LDL in the CBCR group (p = 0.012). Triglycerides in intermediate-density lipoprotein (IDL-TG) increased only in the CBCR group (p = 0.043). The triglyceride-to-HDL (TG/HDL) ratio decreased only in the CTR group (p = 0.006). The TG/HDL ratio was correlated with GlycA (Spearman's correlation coefficient: 0.558, p < 0.001) but not with CRP (p = 0.101). CONCLUSIONS: Our results showed that a 10-month CTR program reduced GlycA levels, the TG/HDL ratio and avoided unfavourable long-term changes in lipoprotein particle composition. Registration at http://ClinicalTrials.gov. NCT number: 04942977.

Modeling the Prognostic Impact of Circulating Tumor Cells Enumeration in Metastatic Breast Cancer for Clinical Trial Design Simulation.

Despite the strong prognostic stratification of circulating tumor cells (CTCs) enumeration in metastatic breast cancer (MBC), current clinical trials usually do not include a baseline CTCs in their design. This study aimed to generate a classifier for CTCs prognostic simulation in existing datasets for hypothesis generation in patients with MBC. A K-nearest neighbor machine learning algorithm was trained on a pooled dataset comprising 2436 individual MBC patients from the European Pooled Analysis Consortium and the MD Anderson Cancer Center to identify patients likely to have CTCs ≥ 5/7 mL blood (StageIVaggressive vs StageIVindolent). The model had a 65.1% accuracy and its prognostic impact resulted in a hazard ratio (HR) of 1.89 (Simulatedaggressive vs SimulatedindolentP < .001), similar to patients with actual CTCs enumeration (HR 2.76; P < .001). The classifier's performance was then tested on an independent retrospective database comprising 446 consecutive hormone receptor (HR)-positive HER2-negative MBC patients. The model further stratified clinical subgroups usually considered prognostically homogeneous such as patients with bone-only or liver metastases. Bone-only disease classified as Simulatedaggressive had a significantly worse overall survival (OS; P < .0001), while patients with liver metastases classified as Simulatedindolent had a significantly better prognosis (P < .0001). Consistent results were observed for patients who had undergone CTCs enumeration in the pooled population. The differential prognostic impact of endocrine- (ET) and chemotherapy (CT) was explored across the simulated subgroups. No significant differences were observed between ET and CT in the overall population, both in terms of progression-free survival (PFS) and OS. In contrast, a statistically significant difference, favoring CT over ET was observed among Simulatedaggressive patients (HR: 0.62; P = .030 and HR: 0.60; P = .037, respectively, for PFS and OS).

The clinical use of circulating tumor cells (CTCs) enumeration for staging of metastatic breast cancer (MBC): International expert consensus paper.

BACKGROUND: The heterogeneity of metastatic breast cancer (MBC) necessitates novel biomarkers allowing stratification of patients for treatment selection and drug development. We propose to use the prognostic utility of circulating tumor cells (CTCs) for stratification of patients with stage IV disease. METHODS: In a retrospective, pooled analysis of individual patient data from 18 cohorts, including 2436 MBC patients, a CTC threshold of 5 cells per 7.5 ml was used for stratification based on molecular subtypes, disease location, and prior treatments. Patients with ≥ 5 CTCs were classified as Stage IVaggressive, those with < 5 CTCs as Stage IVindolent. Survival was analyzed using Kaplan-Meier curves and the log rank test. RESULTS: For all patients, Stage IVindolent patients had longer median overall survival than those with Stage IVaggressive (36.3 months vs. 16.0 months, P < 0.0001) and similarly for de novo MBC patients (41.4 months Stage IVindolent vs. 18.7 months Stage IVaggressive, p < 0.0001). Moreover, patients with Stage IVindolent disease had significantly longer overall survival across all disease subtypes compared to the aggressive cohort: hormone receptor-positive (44 months vs. 17.3 months, P < 0.0001), HER2-positive (36.7 months vs. 20.4 months, P < 0.0001), and triple negative (23.8 months vs. 9.0 months, P < 0.0001). Similar results were obtained regardless of prior treatment or disease location. CONCLUSIONS: We confirm the identification of two subgroups of MBC, Stage IVindolent and Stage IVaggressive, independent of clinical and molecular variables. Thus, CTC count should be considered an important tool for staging of advanced disease and for disease stratification in prospective clinical trials.

Mejora del tratamiento de la dislipemia para pacientes con muy alto riesgo cardiovascular en la práctica clínica. Proyecto COLIPAR / Improvement in the management of dyslipidemia in a clinical practice population at very high cardiovascular risk. The COLIPAR project

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Circulating Tumor Cells in Breast Cancer Patients Treated by Neoadjuvant Chemotherapy: A Meta-analysis.

Background: We conducted a meta-analysis in nonmetastatic breast cancer patients treated by neoadjuvant chemotherapy (NCT) to assess the clinical validity of circulating tumor cell (CTC) detection as a prognostic marker. Methods: We collected individual patient data from 21 studies in which CTC detection by CellSearch was performed in early breast cancer patients treated with NCT. The primary end point was overall survival, analyzed according to CTC detection, using Cox regression models stratified by study. Secondary end points included distant disease-free survival, locoregional relapse-free interval, and pathological complete response. All statistical tests were two-sided. Results: Data from patients were collected before NCT (n = 1574) and before surgery (n = 1200). CTC detection revealed one or more CTCs in 25.2% of patients before NCT; this was associated with tumor size (P < .001). The number of CTCs detected had a detrimental and decremental impact on overall survival (P < .001), distant disease-free survival (P < .001), and locoregional relapse-free interval (P < .001), but not on pathological complete response. Patients with one, two, three to four, and five or more CTCs before NCT displayed hazard ratios of death of 1.09 (95% confidence interval [CI] = 0.65 to 1.69), 2.63 (95% CI = 1.42 to 4.54), 3.83 (95% CI = 2.08 to 6.66), and 6.25 (95% CI = 4.34 to 9.09), respectively. In 861 patients with full data available, adding CTC detection before NCT increased the prognostic ability of multivariable prognostic models for overall survival (P < .001), distant disease-free survival (P < .001), and locoregional relapse-free interval (P = .008). Conclusions: CTC count is an independent and quantitative prognostic factor in early breast cancer patients treated by NCT. It complements current prognostic models based on tumor characteristics and response to therapy.

Clinical validity of circulating tumour cells in patients with metastatic breast cancer: a pooled analysis of individual patient data.

BACKGROUND: We aimed to assess the clinical validity of circulating tumour cell (CTC) quantification for prognostication of patients with metastatic breast cancer by undertaking a pooled analysis of individual patient data. METHODS: We contacted 51 European centres and asked them to provide reported and unreported anonymised data for individual patients with metastatic breast cancer who participated in studies between January, 2003, and July, 2012. Eligible studies had participants starting a new line of therapy, data for progression-free survival or overall survival, or both, and CTC quantification by the CellSearch method at baseline (before start of new treatment). We used Cox regression models, stratified by study, to establish the association between CTC count and progression-free survival and overall survival. We used the landmark method to assess the prognostic value of CTC and serum marker changes during treatment. We assessed the added value of CTCs or serum markers to prognostic clinicopathological models in a resampling procedure using likelihood ratio (LR) χ(2) statistics. FINDINGS: 17 centres provided data for 1944 eligible patients from 20 studies. 911 patients (46·9%) had a CTC count of 5 per 7·5 mL or higher at baseline, which was associated with decreased progression-free survival (hazard ratio [HR] 1·92, 95% CI 1·73-2·14, p<0·0001) and overall survival (HR 2·78, 95% CI 2·42-3·19, p<0·0001) compared with patients with a CTC count of less than 5 per 7·5 mL at baseline. Increased CTC counts 3-5 weeks after start of treatment, adjusted for CTC count at baseline, were associated with shortened progression-free survival (HR 1·85, 95% CI 1·48-2·32, p<0·0001) and overall survival (HR 2·26, 95% CI 1·68-3·03) as were increased CTC counts after 6-8 weeks (progression-free survival HR 2·20, 95% CI 1·66-2·90, p<0·0001; overall survival HR 2·91, 95% CI 2·01-4·23, p<0·0001). Survival prediction was significantly improved by addition of baseline CTC count to the clinicopathological models (progression-free survival LR 38·4, 95% CI 21·9-60·3, p<0·0001; overall survival LR 64·9, 95% CI 41·3-93·4, p<0·0001). This model was further improved by addition of CTC change at 3-5 weeks (progression-free survival LR 8·2, 95% CI 0·78-20·4, p=0·004; overall survival LR 11·5, 95% CI 2·6-25·1, p=0·0007) and at 6-8 weeks (progression-free survival LR 15·3, 95% CI 5·2-28·3; overall survival LR 14·6, 95% CI 4·0-30·6; both p<0·0001). Carcinoembryonic antigen and cancer antigen 15-3 concentrations at baseline and during therapy did not add significant information to the best baseline model. INTERPRETATION: These data confirm the independent prognostic effect of CTC count on progression-free survival and overall survival. CTC count also improves the prognostication of metastatic breast cancer when added to full clinicopathological predictive models, whereas serum tumour markers do not. FUNDING: Janssen Diagnostics, the Nuovo-Soldati foundation for cancer research.

External quality assurance of circulating tumor cell enumeration using the CellSearch(®) system: a feasibility study.

BACKGROUND: Circulating tumor cells (CTCs) are cells that have detached from solid tumors and entered the blood. CTCs can be detected, among others, by semi-automated immunomagnetic enrichment and image cytometry using CellSearch® (Veridex, Raritan, NJ). We studied the feasibility of external quality assurance (EQA) of the entire CellSearch procedure from blood draw to interpretation of results in multiple laboratories. METHODS: Blood samples from six cancer patients and controls were distributed to 14 independent laboratories to test between-laboratory, between-assay, and between-instrument variation. Additionally, between-operator variability was assessed through the interpretation of blinded images of all blood samples on a website. RESULTS: Shipment and storage of samples had no influence on CTC values. Between-instrument (coefficient of variation (CV) < 12%) and between-assay variation was low (CV ≤ 20%), indicating high reproducibility. However, between-laboratory CV ranged from 45 to 64%. Although inter-operator agreement on image interpretation (Fleiss' κ statistics) ranged from "substantial" to "almost perfect," image interpretation, particularly of samples containing high numbers of apoptotic cells, was the main contributor to between-laboratory variation. CONCLUSIONS: This multicenter study shows the feasibility of an EQA program for CTC detection in patient samples, and the importance of continuation of such a program for the harmonization of CTC enumeration.