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Le Mans, France

Denis F.,Jean Bernard Center | Denis F.,University of Rouen | Viger L.,University of Rouen | Charron A.,Jean Bernard Center | And 2 more authors.
Supportive Care in Cancer | Year: 2014

Purpose: We aimed to assess if patients' ratings of symptoms can be used to provide an early indication of disease recurrence or progression in lung cancer. We proposed a simple self-evaluation form made of six clinical parameters weekly scored by patients at home as a follow-up - here named sentinel - to improve relapse detection. Its performances were compared to those of a routine imaging follow-up. Methods: Patients with lung cancer were prospectively recruited to weekly fill a form at home for self-assessing weight, fatigue, pain, appetite, cough, and breathlessness during at least 4 months. Each patient reported weight and assessed the severity of each symptom by grading it from 0 (no symptom) to 3 (major symptom). A score was retrospectively designed for discriminating patients with relapse from those without. Accuracy of relapse detection was then compared to values of the routine planned imaging. Results: Forty-three patients were included in our center and recruited for 16 weeks or more follow-up during which at least one tumor imaging assessment was performed (CT scan or PET-CT). Forty-one completed the form weekly. Sensitivity, specificity, and positive and negative predictive values of sentinel were high (86, 93, 86 % and 93 vs 79, 96, 92, and 90 % for routine imaging - p = ns) and well correlated with relapse (pχ2 > 0.001). Moreover, relapses were detectable with sentinel on average 6 weeks earlier than the planned imaging. Conclusion: This study suggests that a personalized cancer follow-up based on a weekly self-evaluation of six symptoms is feasible and may be accurate for earlier detection of lung cancer relapse, allowing integration in electronic devices for real-time patient outcome follow-up. © 2013 Springer-Verlag Berlin Heidelberg.

Roulland S.,Aix - Marseille University | Kelly R.S.,Imperial College London | Morgado E.,Aix - Marseille University | Sungalee S.,Aix - Marseille University | And 52 more authors.
Journal of Clinical Oncology | Year: 2014

Purpose: The (14;18) translocation constitutes both a genetic hallmark and critical early event in the natural history of follicular lymphoma (FL). However, t(14;18) is also detectable in the blood of otherwise healthy persons, and its relationship with progression to disease remains unclear. Here we sought to determine whether t(14;18)-positive cells in healthy individuals represent tumor precursors and whether their detection could be used as an early predictor for FL. Participants and Methods: Among 520,000 healthy participants enrolled onto the EPIC (European Prospective Investigation Into Cancer and Nutrition) cohort, we identified 100 who developed FL 2 to 161 months after enrollment. Prediagnostic blood from these and 218 controls were screened for t(14;18) using sensitive polymerase chain reaction-based assays. Results were subsequently validated in an independent cohort (65 case participants; 128 controls). Clonal relationships between t(14;18) cells and FL were also assessed by molecular backtracking of paired prediagnostic blood and tumor samples. Results: Clonal analysis of t(14;18) junctions in paired prediagnostic blood versus tumor samples demonstrated that progression to FL occurred from t(14;18)-positive committed precursors. Furthermore, healthy participants at enrollment who developed FL up to 15 years later showed a markedly higher t(14;18) prevalence and frequency than controls (P < .001). Altogether, we estimated a 23-fold higher risk of subsequent FL in blood samples associated with a frequency > 10-4 (odds ratio, 23.17; 95% CI, 9.98 to 67.31; P < .001). Remarkably, risk estimates remained high and significant up to 15 years before diagnosis. Conclusion: High t(14;18) frequency in blood from healthy individuals defines the first predictive biomarker for FL, effective years before diagnosis. © 2014 by American Society of Clinical Oncology.

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