How to improve RCHOP as frontline therapy for diffuse large B-cell lymphoma: a systematic review and meta-analysis of 21 randomized controlled trials

RCHOP is the standard of care for patients with diffuse large b-cell lymphoma (DLBCL) but failures occur in approximately 40% of them. We performed a meta-analysis of 21 randomized controlled trials (RCTs) comparing experimental regimens with RCHOP. We searched the database of PubMed with proper criteria, and data of efficacy (Progression Free Survival-PFS) in the ITT population were extracted and analyzed. Cross comparisons of RCTs were performed by using the CINEMA software. Odds ratio (OR) and 95% confidence intervals (95%, CI) are reported. The literature search yielded 21 RCTs including 5785 patients in the RCHOP arm and 5648 patients in the experimental arm. Odds ratio (OR) for PFS in the total cohort was OR (95%, CI): 0.87 (0.76-0.99), p=0.02. Among different strategies to improve RCHOP, addition of a novel agent on RCHOP improved PFS. In total 1740 patients in the RCHOP arm were compared with 1755 in the RCHOP plus a novel agent arm, and the OR (95% CI) for PFS was 0.84 (0.71-0.97), p=0.02. Indirect comparisons of nine studies adding a novel agent on RCHOP does not give prominence to any agent. Subgroup analysis according to cell of origin was performed for non-GC DLBCL patients. In this subgroup, 1546 patients treated with RCHOP were compared with 1538 patients treated with experimental regimens. The OR (95% CI) for PFS was 0.86 (0.73-1.02), p=0.34. Overall survival data extracted from 18 studies showed no superiority of experimental regimens over RCHOP. Efficacy of RCHOP backbone is marginally improved when adding a novel anti-lymphoma agent.

Performance, Correlation and Kinetic Profile of Circulating Serum Fungal Biomarkers of Invasive Aspergillosis in High-Risk Patients with Hematologic Malignancies

As conventional microbiological documentation of invasive aspergillosis (IA) is difficult to obtain, serum fungal biomarkers are important adjunctive diagnostic tools. Positivity rates and the kinetic profiles of galactomannan (GM), 1,3-β-D-glucan (BDG) and Aspergillus DNA (PCR) were studied in high-risk patients with hematologic malignancies. GM, BDG and PCR data from serial serum specimens (n = 240) from 93 adult hematology patients with probable (n = 8), possible (n = 25) and no (n = 60) IA were retrospectively analyzed. Positivity rates and sensitivity/specificity/positive/negative predictive values (NPV) of each fungal biomarker alone and in combination were estimated. The three markers were compared head-to-head and correlated with various biochemical, demographic and patient characteristics. The positivity rates for patients with probable/possible/no IA were 88%/8%/0% for GM (X² = 55, p < 0.001), 62%/46%/35% for BDG (X² = 2.5, p = 0.29), 62%/33%/27% for PCR (X² = 3.9, p = 0.15), 50%/4%/0% for GM + BDG and GM + PCR (X² = 31, p < 0.001), 50%/8%/22% for BDG + PCR (X² = 6.5, p = 0.038) and 38%/4%/0% for GM + BDG + PCR (X² = 21, p < 0.001). Higher agreement (76%) and negative correlation (r_s = −0.47, p = 0.0017) was found between GM index and PCR Ct values. The sensitivity and NPV was 45–55% and 90–92% when biomarkers assessed alone and increased to 75–90% and 93–97%, respectively when combined. Weak significant correlations were found between GM, PCR and BDG results with renal/liver function markers (r = 0.11–0.57) with most GM+ and PCR+ samples found in the first and second week of clinical assessment, respectively and BDG later on. Different positivity rates, time profiles and performances were found for the three biomarkers advocating the combination of GM with PCR for the early diagnosis of IA, whereas the high NPV of combined biomarkerscould help excluding IA.