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3.
J Clin Oncol ; 42(5): 550-561, 2024 Feb 10.
Article in English | MEDLINE | ID: mdl-38096461

ABSTRACT

PURPOSE: We report an analysis of minimal residual/detectable disease (MRD) as a predictor of outcome in previously untreated patients with follicular lymphoma (FL) from the randomized, multicenter GALLIUM (ClinicalTrials.gov identifier: NCT01332968) trial. PATIENTS AND METHODS: Patients received induction with obinutuzumab (G) or rituximab (R) plus bendamustine, or cyclophosphamide, doxorubicin, vincristine, prednisone (CHOP) or cyclophosphamide, vincristine, prednisone (CVP) chemotherapy, followed by maintenance with the same antibody in responders. MRD status was assessed at predefined time points (mid-induction [MI], end of induction [EOI], and at 4-6 monthly intervals during maintenance and follow-up). Patients with evaluable biomarker data at diagnosis were included in the survival analysis. RESULTS: MRD positivity was associated with inferior progression-free survival (PFS) at MI (hazard ratio [HR], 3.03 [95% CI, 2.07 to 4.45]; P < .0001) and EOI (HR, 2.25 [95% CI, 1.53 to 3.32]; P < .0001). MRD response was higher after G- versus R-chemotherapy at MI (94.2% v 88.9%; P = .013) and at EOI (93.1% v 86.7%; P = .0077). Late responders (MI-positive/EOI-negative) had a significantly poorer PFS than early responders (MI-negative/EOI-negative; HR, 3.11 [95% CI, 1.75 to 5.52]; P = .00011). The smallest proportion of MRD positivity was observed in patients receiving bendamustine at MI (4.8% v 16.0% in those receiving CHOP; P < .0001). G appeared to compensate for less effective chemotherapy regimens, with similar MRD response rates observed across the G-chemo groups. During the maintenance period, more patients treated with R than with G were MRD-positive (R-CHOP, 20.7% v G-CHOP, 7.0%; R-CVP, 21.7% v G-CVP, 9.4%). Throughout maintenance, MRD positivity was associated with clinical relapse. CONCLUSION: MRD status can determine outcome after induction and during maintenance, and MRD negativity is a prerequisite for long-term disease control in FL. The higher MRD responses after G- versus R-based treatment confirm more effective tumor cell clearance.


Subject(s)
Gallium , Lymphoma, Follicular , Humans , Antineoplastic Combined Chemotherapy Protocols/adverse effects , Bendamustine Hydrochloride , Cyclophosphamide , Doxorubicin , Gallium/therapeutic use , Neoplasm, Residual/drug therapy , Prednisone , Rituximab , Vincristine
4.
Leukemia ; 34(2): 522-532, 2020 02.
Article in English | MEDLINE | ID: mdl-31462735

ABSTRACT

We report assessment of minimal residual disease (MRD) status and its association with outcome in rituximab-refractory follicular lymphoma (FL) in the randomized GADOLIN trial (NCT01059630). Patients received obinutuzumab (G) plus bendamustine (Benda) induction followed by G maintenance, or Benda induction alone. Patients with a clonal marker (t[14;18] translocation and/or immunoglobulin heavy or light chain rearrangement) detected at study screening were assessed for MRD at mid-induction (MI), end of induction (EOI), and every 6-24 months post-EOI/discontinuation by real-time quantitative PCR. At MI, 41/52 (79%) patients receiving G-Benda were MRD-negative vs. 17/36 (47%) patients receiving Benda alone (p = 0.0029). At EOI, 54/63 (86%) patients receiving G-Benda were MRD-negative vs. 30/55 (55%) receiving Benda alone (p = 0.0002). MRD-negative patients at EOI had improved progression-free survival (HR, 0.33, 95% CI, 0.19-0.56, p < 0.0001) and overall survival (HR, 0.39, 95% CI, 0.19-0.78, p = 0.008) vs. MRD-positive patients, and maintained their MRD-negative status for longer if they received G maintenance than if they did not. These results suggest that the addition of G to Benda-based treatment during induction can significantly contribute to the speed and depth of response, and G maintenance in MRD-negative patients potentially delays lymphoma regrowth.


Subject(s)
Antineoplastic Combined Chemotherapy Protocols/therapeutic use , Lymphoma, Follicular/drug therapy , Neoplasm, Residual/drug therapy , Adult , Aged , Aged, 80 and over , Antibodies, Monoclonal, Humanized/administration & dosage , Bendamustine Hydrochloride/administration & dosage , Female , Humans , Lymphoma, Non-Hodgkin/drug therapy , Male , Middle Aged , Progression-Free Survival , Rituximab/administration & dosage
7.
Obes Facts ; 5(1): 77-90, 2012.
Article in English | MEDLINE | ID: mdl-22433620

ABSTRACT

OBJECTIVE: The aim of this study was to define body fat percentiles for German children and adolescents aged 3-16 years using the largest German database. METHODS: The study population included 11,632 girls and 11,604 boys. Data were pooled from: i) Kiel Obesity Prevention Study (KOPS), acquisition period: 1996-2008, n = 12,237; ii) 'Better diet. More exercise. KINDERLEICHT-REGIONS', acquisition period: 2007, n = 9,405; and iii) examination of Jena schoolchildren, acquisition period: 2005, n = 1,594. Body fat mass was measured by bioelectrical impedance analysis using a population-specific algorithm. Data were weighted to achieve a representative sample for Germany. Percentile curves were constructed by the LMS method and proved by Worm plots and Q-statistic. RESULTS: In both genders, the higher body fat percentile curves sloped downwards to age 7 years, whereas the lower percentiles declined up to 8.5 years. Thereafter fat mass remained nearly constant with age in boys and increased in girls. The 10th percentile achieved a minimum of 10-11% body fat in both genders, whereas the 90th percentile curve fluctuated between 29 and 44% in boys or 30-43% in girls. The association between fat mass and blood pressure was too weak to define disease-related cut-offs. CONCLUSION: These body fat percentiles are suitable reference values for German children and adolescents.


Subject(s)
Adipose Tissue , Body Composition , Obesity/diagnosis , Adolescent , Age Factors , Algorithms , Blood Pressure , Child , Child, Preschool , Electric Impedance , Female , Germany/epidemiology , Humans , Male , Obesity/epidemiology , Reference Values , Sex Factors , Statistical Distributions
8.
Pediatrics ; 130(4): e865-71, 2012 Oct.
Article in English | MEDLINE | ID: mdl-22945402

ABSTRACT

OBJECTIVE: Calculation of attributable risks (ARs) of childhood overweight to estimate effectiveness of prevention strategies. METHODS: We used pooled data of 4 population-based German studies including 34240 children and adolescents aged 3 to 18 years to calculate the impact of familial, social, "early life", and lifestyle factors on overweight. ARs (joint for all determinants as well as partial risks) were calculated. RESULTS: The prevalence of childhood overweight was 13.4%. Successfully tackling all determinants can reduce overweight by 77.7% (ie, from 13.4% to 3.0%; = joint AR) with partial effects of treating parental overweight (42.5%); improving social status (14.3%); reducing media time to <1 hour per day (11.4%); and not smoking during pregnancy, low weight gain during pregnancy, and breastfeeding (together 9.5%), respectively. Improving all preventable risk factors (ie, early life factors and lifestyle) the effect is 9.2%. Media time has the strongest effect. CONCLUSIONS: The determinants identified explained 78% of the prevalence of overweight. Taking into account the partial ARs, the effectiveness of lifestyle interventions to prevent overweight in children is limited. Our data argue in favor of interventions aimed at families and social environments, with a major focus on promoting a lower screen time and computer use in children.


Subject(s)
Overweight/etiology , Adolescent , Breast Feeding , Child , Child, Preschool , Cross-Sectional Studies , Female , Germany/epidemiology , Health Behavior , Health Surveys , Humans , Logistic Models , Male , Multivariate Analysis , Odds Ratio , Overweight/epidemiology , Overweight/prevention & control , Pregnancy , Prenatal Exposure Delayed Effects/epidemiology , Prenatal Exposure Delayed Effects/etiology , Prenatal Exposure Delayed Effects/prevention & control , Prevalence , Primary Prevention , Risk Factors , Sedentary Behavior , Self Report , Smoking/adverse effects , Socioeconomic Factors
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