Factors Affecting the Clinical Course of Follicular Lymphoma: A Multistate Survival Analysis Using Individual Patient Data from Eight Multicenter Randomized Clinical Trials.

INTRODUCTION/BACKGROUND: Leveraging the Follicular Lymphoma Analysis of Surrogacy Hypothesis database of individual patient data from first-line clinical trials, we studied the clinical course of follicular lymphoma (FL) and investigated clinical factors associated with FL outcomes. PATIENTS AND METHODS: We examined 2428 patients from 8 randomized trials using multistate survival models with 4 states: induction treatment, progression, death from FL, and death from other causes. We utilized Aalen-Johansen estimator and Cox models to assess the likelihood of FL outcomes and quantify predictors' effects. RESULTS: Two-year progression, FL-related death, and death from other causes estimates were 26.5%, 3.4% and 1.4%, respectively. FL-associated deaths were the primary cause of mortality within 10 years of follow-up. Male sex (hazard ratio: 1.25; 95% confidence interval: 1.05-1.47), > 4 involved nodal areas (1.51; 1.23-1.86), elevated LDH (1.20; 1.01-1.43), low hemoglobin (1.44; 1.15-1.81), and elevated ß-2 levels (1.23; 1.02-1.47) increased risk of progression. CD20-targeting agents reduced risks for progression (0.29; 0.22-0.39), death from FL (0.05; 0.01-0.20), and death from other causes without progression (0.13; 0.05-0.33) and following progression (0.52; 0.30-0.92). Estimated 2-year progression rates were 22.3% and 43.5% with or without CD20-targeting agents, respectively. Two-year FL-associated mortality rate was 8.3% among patients without CD20-targeting agents, 5.4% with B-symptoms, 4.9% with elevated LDH, and 9.1% with low hemoglobin. CONCLUSION: This study identified independent contributions of baseline clinical factors to distinct outcomes for patients with FL following first-line therapy on a clinical trial. Similar analytical approaches are needed to increase understanding of factors that influence FL outcomes in other settings.

Staffing and Capacity Planning for SARS-CoV-2 Monoclonal Antibody Infusion Facilities: A Performance Estimation Calculator Based on Discrete-Event Simulations.

Background: The COVID-19 pandemic has significantly stressed healthcare systems. The addition of monoclonal antibody (mAb) infusions, which prevent severe disease and reduce hospitalizations, to the repertoire of COVID-19 countermeasures offers the opportunity to reduce system stress but requires strategic planning and use of novel approaches. Our objective was to develop a web-based decision-support tool to help existing and future mAb infusion facilities make better and more informed staffing and capacity decisions. Materials and Methods: Using real-world observations from three medical centers operating with federal field team support, we developed a discrete-event simulation model and performed simulation experiments to assess performance of mAb infusion sites under different conditions. Results: 162,000 scenarios were evaluated by simulations. Our analyses revealed that it was more effective to add check-in staff than to add additional nurses for middle-to-large size sites with ≥2 infusion nurses; that scheduled appointments performed better than walk-ins when patient load was not high; and that reducing infusion time was particularly impactful when load on resources was only slightly above manageable levels. Discussion: Physical capacity, check-in staff, and infusion time were as important as nurses for mAb sites. Health systems can effectively operate an infusion center under different conditions to provide mAb therapeutics even with relatively low investments in physical resources and staff. Conclusion: Simulations of mAb infusion sites were used to create a capacity planning tool to optimize resource utility and allocation in constrained pandemic conditions, and more efficiently treat COVID-19 patients at existing and future mAb infusion sites.

A population-based multistate model for diffuse large B-cell lymphoma-specific mortality in older patients.

BACKGROUND: Despite effective therapies, outcomes for diffuse large B-cell lymphoma (DLCBL) remain heterogeneous in older individuals due to comorbid diseases and variations in disease biology. METHODS: Using the Surveillance, Epidemiology, and End Results (SEER)-Medicare database, the authors conducted a multistate survival analysis of 11,780 patients with DLBCL who were aged ≥65 years at the time of diagnosis (2002-2009). Cox proportional hazards models were used to specify the impact of prognostic factors on overall survival and cause-specific deaths, and the Aalen-Johansen estimator was used to project the course of DLBCL over time with or without standard therapy with rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP). RESULTS: Advanced age (hazard ratio [HR] for ages 71-75 years: 1.25; HR for ages 76-80 years: 1.46; HR for ages 81-85 years: 1.88; and HR for age ≥86 years: 2.26), DLBCL stage (HR for Ann Arbor stage II: 1.28; HR for stage III: 1.54; and HR for stage IV: 1.95), Charlson Comorbidity Index (CCI) ≥1 (HR for CCI of 1, 1.15; and HR for CCI >1, 1.37), and not being married (HR, 1.12) were associated with an increased risk of DLBCL-specific death. Being female (HR, 0.91) and of higher socioeconomic status (HR, 0.91) were associated with a lower risk of DLBCL-related mortality after therapy. For patients treated with R-CHOP (3610 patients), the risk of death due to DLBCL was 14.0% and 18.6%, respectively, at 2 and 5 years of treatment and plateaued afterward, confirming a 5-year "cure" point while receiving R-CHOP among older patients. CONCLUSIONS: Conducting a survival analysis over a large data set, the current study evaluated competing risks for death within a multistate modeling framework, and identified age, sex, and CCI as risk factors for DLBCL-specific and other causes of death.

Assessing the Effectiveness of Treatment Sequences for Older Patients With High-risk Follicular Lymphoma With a Multistate Model.

BACKGROUND: Disease progression within < 2 years of initial chemoimmunotherapy and patient age > 60 years have been associated with poor overall survival (OS) in follicular lymphoma (FL). No standard treatment exists for these high-risk patients, and the effectiveness of sequential therapies remains unclear. PATIENTS AND METHODS: We studied the course of FL with first-, second-, and third-line treatment. Using large population-based data, we identified 5234 patients with FL diagnosed in 2000 to 2009. Of these patients, 71% had received second-line therapy < 2 years, and 29% had received no therapy after first-line therapy, with a median OS of < 3 years. Treatment included rituximab, R-CVP (rituximab, cyclophosphamide, vincristine), R-CHOP (rituximab, cyclophosphamide, hydroxydaunorubicin, vincristine), R-Other (other rituximab-containing), and other regimens. The Aalen-Johansen estimator and Cox proportional hazards models were used to quantify the outcomes and assess the effects of the clinical and sociodemographic factors. RESULTS: R-CHOP demonstrated the most favorable 5-year OS among first- (71%), second- (55%), and third-line (61%) therapies. First-line R-CHOP improved OS (hazard ratio [HR], 0.57; 95% confidence interval [CI], 0.50-0.64) and reduced the mortality risks after first-line (HR, 0.60; 95% CI, 0.47-0.77), second-line (HR, 0.40; 95% CI, 0.29-0.53), and third-line (HR, 0.63; 95% CI, 0.53-0.76) treatments. B-symptoms, being married, and histologic grade 1/2 were associated with the use of earlier second-line therapy. Early progression from second- to third-line therapy was associated with poor OS. The repeated use of R-CHOP or R-CVP as first- and second-line treatment yielded high 2-year mortality rates (R-CHOP + R-CHOP, 17.3%; R-CVP + R-CVP, 21.1%). CONCLUSION: Our multistate approach assessed the effect of sequential therapy on the immediate and subsequent treatment-line outcomes. We found that R-CHOP in any line improved OS for patients with high-risk FL.

Microsimulation Modeling in Oncology.

PURPOSE: Microsimulation is a modeling technique that uses a sample size of individual units (microunits), each with a unique set of attributes, and allows for the simulation of downstream events on the basis of predefined states and transition probabilities between those states over time. In this article, we describe the history of the role of microsimulation in medicine and its potential applications in oncology as useful tools for population risk stratification and treatment strategy design for precision medicine. METHODS: We conducted a comprehensive and methodical search of the literature using electronic databases-Medline, Embase, and Cochrane-for works published between 1985 and 2016. A medical subject heading search strategy was constructed for Medline searches by using a combination of relevant search terms, such as "microsimulation model medicine," "multistate modeling cancer," and "oncology." RESULTS: Microsimulation modeling is particularly useful for the study of optimal intervention strategies when randomized control trials may not be feasible, ethical, or practical. Microsimulation models can retain memory of prior behaviors and states. As such, it allows an explicit representation and understanding of how various processes propagate over time and affect the final outcomes for an individual or in a population. CONCLUSION: A well-calibrated microsimulation model can be used to predict the outcome of the event of interest for a new individual or subpopulations, assess the effectiveness and cost effectiveness of alternative interventions, and project the future disease burden of oncologic diseases. In the growing field of oncology research, a microsimulation model can serve as a valuable tool among the various facets of methodology available.

Is Nebivolol Really Effective in Preventing Contrast Induced Nephropathy?

BACKGROUND/AIMS: Contrast induced nephropathy (CIN) has multifactorial etiopatogenesis including oxidative stress and vasoconstriction. Nebivolol is an antioxidant and has vasodilatatory effect via NO release and may prevent CIN development. We have noticed that a few number of studies that have evaluated the effectiveness of nebivolol for the prevention of CIN used serum creatinine (sCr) levels for CIN detection. However, sCr is an insensitive marker for renal damage. Therefore in this study we used serum neutrophil-gelatinase associated lipocalin (NGAL), a more sensitive marker of renal damage, to evaluate preventive role of nebivolol in CIN. METHODS: 159 patients undergoing coronary angiography (CAG) who had at least one risk factor for CIN were divided into nebivolol (+) and (-) groups. CIN was defined as a rise in sCr of 0.5mg/dl or a 25% increase from the baseline value. Serum Cr, glomerular filtration rate (eGFR) and NGAL levels were assessed before and 48 h after CAG. Mehran risk scores were calculated for both groups. RESULTS: Both groups were similar in terms of baseline characteristics, Mehran risk scores, and current medications. Clinically, CIN developed at similar rates in both groups. Serum Cr, eGFR and NGAL values were similar in both groups before and after CAG. Serum Cr and NGAL levels increased and eGFR decreased significantly compared to the levels before CAG. Patients who developed CIN were significantly older (p=0.003), and were more likely to have DM (p=0.012), a higher mean contrast agent volume (p<0.001), and a higher Mehran score (p <0.001). We did not observe any favorable effect of Nebivolol in the prevention of CIN in patients undergoing CAG. CONCLUSION: According to the results of our study Nebivolol does not seem to prevent CIN in patients undergoing CAG. However, further randomised controlled trials with more sensitive renal damage markers are obviously needed to understand the actual effect of nebivolol on CIN especially through oxidative pathways and in high risk patients.