Molecular follow-up in gastric mucosa-associated lymphoid tissue lymphomas: early analysis of the LY03 cooperative trial

Gastric marginal zone lymphoma of mucosa-associated lymphoid tissue (MALT)-type can regress after anti-Helicobacter pylori treatment. The International Extranodal Lymphoma Study Group, the United Kingdom Lymphoma Group, and the Groupe d'Etude des Lymphomes de l'Adulte have conducted a trial to ascertain whether the addition of chlorambucil is of benefit after anti-H pylori therapy. At the last interim analysis, 105 (55%) of 189 patients had achieved a complete histologic remission after anti-Helicobacter therapy. To further assess the ability of treatment to eradicate the lymphoma clone, we analyzed the gastric biopsies from a subset of the patients by polymerase chain reaction (PCR) targeted to the immunoglobulin heavy chain genes as a molecular marker for minimal residual disease. Sixty-two cases were examined at diagnosis. Fifty-four cases were monoclonal by PCR. Forty-two of these patients achieved histologic complete remission (hCR) after anti-Helicobacter treatment: 34 cases underwent molecular follow-up analysis. Fifteen patients (44%) were in molecular remission with a median follow-up of 2 years after antibiotic treatment and of 1 year after the achievement of hCR. Less than half of the patients with MALT lymphoma can achieve sustained molecular remission after anti-Helicobacter therapy. The presence of molecular disease in the absence of histologic disease does not appear to be associated with histologic relapse, but, given the indolent nature of MALT lymphomas, a longer follow-up is needed.     

On the joint use of propensity and prognostic scores in estimation of the average treatment effect on the treated: a simulation study

Propensity and prognostic score methods seek to improve the quality of causal inference in non‐randomized or observational studies by replicating the conditions found in a controlled experiment, at least with respect to observed characteristics. Propensity scores model receipt of the treatment of interest; prognostic scores model the potential outcome under a single treatment condition. While the popularity of propensity score methods continues to grow, prognostic score methods and methods combining propensity and prognostic scores have thus far received little attention. To this end, we performed a simulation study that compared subclassification and full matching on a single estimated propensity or prognostic score with three approaches combining the estimated propensity and prognostic scores: full matching on a Mahalanobis distance combining the estimated propensity and prognostic scores (FULL–MAHAL); full matching on the estimated prognostic propensity score within propensity score calipers (FULL–PGPPTY); and subclassification on an estimated propensity and prognostic score grid with 5 × 5 subclasses (SUBCLASS(5*5)). We considered settings in which one, both, or neither score model was misspecified. The data generating mechanisms varied in the degree of linearity and additivity in the true treatment assignment and outcome models. FULL–MAHAL and FULL–PGPPTY exhibited strong to superior performance in root mean square error terms across all simulation settings and scenarios. Methods combining propensity and prognostic scores were no less robust to model misspecification than single‐score methods even when both score models were incorrectly specified. Our findings support the joint use of propensity and prognostic scores in estimation of the average treatment effect on the treated. Copyright © 2013 John Wiley & Sons, Ltd.     

Periodontal disease and quality of life: Umbrella review of systematic reviews

This umbrella review appraised existing systematic reviews and meta‐analysis to establish the impact of periodontal disease and therapy on general and oral health‐related quality of life. A systematic electronic literature search was carried out in accordance with the PRISMA guideline up to January 2020 using PubMed, LIVIVO, EMBASE and OpenGrey (PROSPERO CRD 42020163831). Hand searching was performed through the reference lists of periodontal textbooks and related journals. All English language‐based systematic reviews and meta‐analysis that assessed the impact of periodontal disease and treatment interventions on general and oral health‐related quality of life were included. Overall, eight articles met the inclusion criteria and their methodological quality was assessed using the AMSTAR2 criteria. Two systematic reviews showed a significant impact of oral conditions on general health‐related quality of life, although the specific impact of periodontal disease remains inconclusive. Three systematic reviews established a negative impact of periodontal disease on oral health‐related quality of life. Another three systematic reviews concluded that periodontal treatment can improve oral health‐related quality of life. Oral conditions, like periodontal disease, can impact the general health‐related quality of life. Periodontal disease is negatively correlated with oral health‐related quality of life, although treatment interventions can improve self‐reported quality of life. In view of the heterogeneity of generic instruments currently utilized to assess the self‐reported quality of life of periodontal patients, the development of a general and oral health‐related quality of life instrument specific for periodontal disease is strongly recommended.     

Determining the minimally important difference for the Oral Health Impact Profile-20

In the context of clinical trials, measurement of change is critical. The aim of this study was to determine the minimally important difference (MID) for the Oral Health Impact Profile-20 (OHIP-20) when used with partially dentate patients undergoing treatment that included the provision of removable partial dentures. In a prospective clinical trial, 51 consecutive patients were provided with removable partial dentures. In addition to demographic and dental status data, patients completed an OHIP-20 prior to treatment. One month postoperatively, patients completed a post-treatment OHIP-20 and a global transition scale. Domains assessed in the global transition scale were appearance, ability to chew food, oral comfort, and speech. The MID for the OHIP-20 was calculated using the anchor-based approach. From the initial sample of 51 patients, 44 completed post-treatment questionnaires and were included in the analysis. Change scores in the four transition domains indicated that new dentures had a positive impact in the majority of subjects, especially in perceived impact on chewing and appearance. The study provided a guideline as to what constitutes the MID for the OHIP-20. This benchmark can be used when interpreting the impact of clinical intervention for replacing missing teeth and for power calculation in statistical analyses.     

Kinetic analysis of 3'-deoxy-3'-18F-fluorothymidine in patients with gliomas.

3'-Deoxy-3'-fluorothymidine (FLT), a thymidine analog, is under investigation for monitoring cellular proliferation in gliomas, a potential measure of disease progression and response to therapy. Uptake may result from retention in the biosynthetic pathway or leakage via the disrupted blood-tumor barrier. Visual analysis or static measures of 18F-FLT uptake are problematic as transport and retention cannot be distinguished. METHODS: Twelve patients with primary brain tumors were imaged for 90 min of dynamic 18F-FLT PET with arterial blood sampling. Total blood activity was corrected for labeled metabolites to provide an FLT input function. A 2-tissue compartment, 4-rate-constant model was used to determine blood-to-tissue transport (K1) and metabolic flux (K(FLT)). Modeling results were compared with MR images of blood-brain barrier (BBB) breakdown revealed by gadolinium (Gd) contrast enhancement. Parametric image maps of K1 and K(FLT) were produced by a mixture analysis approach. RESULTS: Similar to prior work with 11C-thymidine, identifiability analysis showed that K1 (transport) and K(FLT) (flux) could be estimated independently for sufficiently high K1 values. However, estimation of K(FLT) was less robust at low K1 values, particularly those close to normal brain. K1 was higher for MRI contrast-enhancing (CE) tumors (0.053 +/- 0.029 mL/g/min) than noncontrast-enhancing (NCE) tumors (0.005 +/- 0.002 mL/g/min; P < 0.02), and K(FLT) was higher for high-grade tumors (0.018 +/- 0.008 mL/g/min, n = 9) than low-grade tumors (0.003 +/- 0.003 mL/g/min, n = 3; P < 0.01). The flux in NCE tumors was indistinguishable from contralateral normal brain (0.002 +/- 0.001 mL/g/min). For CE tumors, K1 was higher than K(FLT). Parametric images matched region-of-interest estimates of transport and flux. However, no patient has 18F-FLT uptake outside of the volume of increased permeability defined by MRI T1+Gd enhancement. CONCLUSION: Modeling analysis of 18F-FLT PET data yielded robust estimates of K1 and K(FLT) for enhancing tumors with sufficiently high K1 and provides a clearer understanding of the relationship between transport and retention of 18F-FLT in gliomas. In tumors that show breakdown of the BBB, transport dominates 18F-FLT uptake. Transport across the BBB and modest rates of 18F-FLT phosphorylation appear to limit the assessment of cellular proliferation using 18F-FLT to highly proliferative tumors with significant BBB breakdown.     

Contourlet-based hippocampal magnetic resonance imaging texture features for multivariant classification and prediction of Alzheimer’s disease

The study is aimed to assess whether the addition of contourlet-based hippocampal magnetic resonance imaging (MRI) texture features to multivariant models improves the classification of Alzheimer’s disease (AD) and the prediction of mild cognitive impairment (MCI) conversion, and to evaluate whether Gaussian process (GP) and partial least squares (PLS) are feasible in developing multivariant models in this context. Clinical and MRI data of 58 patients with probable AD, 147 with MCI, and 94 normal controls (NCs) were collected. Baseline contourlet-based hippocampal MRI texture features, medical histories, symptoms, neuropsychological tests, volume-based morphometric (VBM) parameters based on MRI, and regional CMgl measurement based on fluorine-18 fluorodeoxyglucose-positron emission tomography were included to develop GP and PLS models to classify different groups of subjects. GPR1 model, which incorporated MRI texture features and was based on GPG, performed better in classifying different groups of subjects than GPR2 model, which used the same algorithm and had the same data as GPR1 except that MRI texture features were excluded. PLS model, which included the same variables as GPR1 but was based on the PLS algorithm, performed best among the three models. GPR1 accurately predicted 82.2% (51/62) of MCI convertors confirmed during the 2-year follow-up period, while this figure was 53 (85.5%) for PLS model. GPR1 and PLS models accurately predicted 58 (79.5%) vs. 61 (83.6%) of 73 patients with stable MCI, respectively. For seven patients with MCI who converted to NCs, PLS model accurately predicted all cases (100%), while GPR1 predicted six (85.7%) cases. The addition of contourlet-based MRI texture features to multivariant models can effectively improve the classification of AD and the prediction of MCI conversion to AD. Both GPR and LPS models performed well in the classification and predictive process, with the latter having significantly higher classification and predictive accuracies. Advances in knowledge: We combined contourlet-based hippocampal MRI texture features, medical histories, symptoms, neuropsychological tests, volume-based morphometric (VBM) parameters, and regional CMgl measurement to develop models using GP and PLS algorithms to classify AD patients.