Survival analysis of Stage IIA1 and IIA2 cervical cancer patients

AbstractObjectiveThe aim of this study was to assess the benefits of the 2009 International Federation of Gynecology and Obstetrics (FIGO) staging system for survival of patients with Stage IIA1 and IIA2 cervical cancer (Cx Ca).Materials and MethodsA study cohort of 51 patients with Stage IIA Cx Ca was retrospectively collected from the 2004–2009 hospital-based, long-form Cx Ca data registry at Mackay Memorial Hospital (Taipei, Taiwan). The survivorship and overall survival were compared between these two groups (Stages IIA1 and IIA2) using log-rank test.ResultsThirty-six and 15 patients were classified into Stages IIA1 and IIA2, respectively. Stage IIA2 patients were younger than those with Stage IIA1 disease (mean age, 47.4 vs. 55.1 years, p = 0.008), but no significant difference was observed in confirmed pelvic lymph node status (21.4% vs. 38.5%, p = 0.280) between them. Although the 2-year and 5-year overall survival was better among Stage IIA1 patients, there was no significant difference in survival between Stage IIA1 and IIA2 groups (2-year, 90.6% vs. 77.8%; 5-year, 86.3% vs. 51.9%, p = 0.218).ConclusionAlthough there was a trend in survival difference between Stage IIA1 and IIA2 patients, the difference was not statistically significant. The revised FIGO 2009 staging system for Cx Ca defines a group of Stage IIA patients with bulky tumor (Stage IIA2) that are generally younger than Stage IIA1 patients. It is sensible to investigate an alternate or enhanced treatment scheme for Stage IIA2 patients. Ideally, the treatment scheme should prevent unnecessary radical surgery if a patient can be exposed to either chemotherapy or radiotherapy, alone or in combination

Nonlinear gyrokinetic simulations of the I-mode high confinement regime and comparisons with experimenta)

For the first time, nonlinear gyrokinetic simulations of I-mode plasmas are performed and compared with experiment. I-mode is a high confinement regime, featuring energy confinement similar to H-mode, but without enhanced particle and impurity particle confinement [D. G. Whyte et al., Nucl. Fusion 50, 105005 (2010)]. As a consequence of the separation between heat and particle transport, I-mode exhibits several favorable characteristics compared to H-mode. The nonlinear gyrokinetic code GYRO [J. Candy and R. E. Waltz, J Comput. Phys. 186, 545 (2003)] is used to explore the effects of E × B shear and profile stiffness in I-mode and compare with L-mode. The nonlinear GYRO simulations show that I-mode core ion temperature and electron temperature profiles are more stiff than L-mode core plasmas. Scans of the input E × B shear in GYRO simulations show that E × B shearing of turbulence is a stronger effect in the core of I-mode than L-mode. The nonlinear simulations match the observed reductions in long wavelength density fluctuation levels across the L-I transition but underestimate the reduction of long wavelength electron temperature fluctuation levels. The comparisons between experiment and gyrokinetic simulations for I-mode suggest that increased E × B shearing of turbulence combined with increased profile stiffness are responsible for the reductions in core turbulence observed in the experiment, and that I-mode resembles H-mode plasmas more than L-mode plasmas with regards to marginal stability and temperature profile stiffness.United States. Department of Energy (Contract No. DE-FC02-99ER54512-CMOD)United States. Department of Energy. Office of Science (Contract No. DE-AC02- 05CH11231

31st Annual Meeting and Associated Programs of the Society for Immunotherapy of Cancer (SITC 2016) : part two

Background The immunological escape of tumors represents one of the main ob- stacles to the treatment of malignancies. The blockade of PD-1 or CTLA-4 receptors represented a milestone in the history of immunotherapy. However, immune checkpoint inhibitors seem to be effective in specific cohorts of patients. It has been proposed that their efficacy relies on the presence of an immunological response. Thus, we hypothesized that disruption of the PD-L1/PD-1 axis would synergize with our oncolytic vaccine platform PeptiCRAd. Methods We used murine B16OVA in vivo tumor models and flow cytometry analysis to investigate the immunological background. Results First, we found that high-burden B16OVA tumors were refractory to combination immunotherapy. However, with a more aggressive schedule, tumors with a lower burden were more susceptible to the combination of PeptiCRAd and PD-L1 blockade. The therapy signifi- cantly increased the median survival of mice (Fig. 7). Interestingly, the reduced growth of contralaterally injected B16F10 cells sug- gested the presence of a long lasting immunological memory also against non-targeted antigens. Concerning the functional state of tumor infiltrating lymphocytes (TILs), we found that all the immune therapies would enhance the percentage of activated (PD-1pos TIM- 3neg) T lymphocytes and reduce the amount of exhausted (PD-1pos TIM-3pos) cells compared to placebo. As expected, we found that PeptiCRAd monotherapy could increase the number of antigen spe- cific CD8+ T cells compared to other treatments. However, only the combination with PD-L1 blockade could significantly increase the ra- tio between activated and exhausted pentamer positive cells (p= 0.0058), suggesting that by disrupting the PD-1/PD-L1 axis we could decrease the amount of dysfunctional antigen specific T cells. We ob- served that the anatomical location deeply influenced the state of CD4+ and CD8+ T lymphocytes. In fact, TIM-3 expression was in- creased by 2 fold on TILs compared to splenic and lymphoid T cells. In the CD8+ compartment, the expression of PD-1 on the surface seemed to be restricted to the tumor micro-environment, while CD4 + T cells had a high expression of PD-1 also in lymphoid organs. Interestingly, we found that the levels of PD-1 were significantly higher on CD8+ T cells than on CD4+ T cells into the tumor micro- environment (p < 0.0001). Conclusions In conclusion, we demonstrated that the efficacy of immune check- point inhibitors might be strongly enhanced by their combination with cancer vaccines. PeptiCRAd was able to increase the number of antigen-specific T cells and PD-L1 blockade prevented their exhaus- tion, resulting in long-lasting immunological memory and increased median survival

An analytics approach to problems in health care

Thesis: Ph. D., Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2017.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student-submitted PDF version of thesis.Includes bibliographical references (pages 99-102).Health care expenditures in the United States have been increasing at unsustainable rates for more than thirty years with no signs of abating. Decisions to accept or reject deceased-donor kidneys offered to patients on the kidney transplantation wait-list currently rely on physician experience and intuition. Scoring rules to determine which end-stage liver disease patients are in most dire need of immediate transplantation have been haphazardly designed and reactively modified in an attempt to decrease waitlist mortality and increase fairness for cancer patients. For each of the above problem settings, we propose a framework that takes real-world data as input and draws upon modern data analytics methods ranging from mixed integer linear optimization to predictive machine learning to yield actionable insights that can add a significant edge over current practice. We describe an approach that, given insurance claims data, leads conservatively to a 10% reduction in health care costs in a study involving a large private US employer. Using historical data for patients on the kidney waitlist and organ match runs, we build a model that achieves an out-of-sample AUC of 0.87 when predicting whether or not a patient will receive a kidney of a particular quality within three, six, or twelve months. Given historical data for patients on the liver waitlist, we create a unified model that is capable of averting an additional 25% of adverse events in simulation compared to current practice without disadvantaging cancer patients.by Jerry Lai Kung.Ph. D

Non-lethal weapons in noncombatant evacuation operations

This thesis examines the utility of non-lethal weapons for mitigating risks in demanding tactical scenarios, specifically crowd control. Noncombatant evacuation operations (NEOs) are conducted when a host government becomes unstable. A NEO force's failure to manage the potential for local violence against the mission can lead to negative consequences for U.S. foreign policy and international relations. Therefore, the NEO force must control any escalation in the threat level because mission success could be jeopardized. Along with restrictive rules of engagement these considerations discourage the use of deadly force. Thus, non-lethal weapons have a role in NEOs. One of the challenges in NEOs is crowd control. Crowds have the potential for violence. Left unchecked, they can endanger the NEO mission. This thesis finds that a non- lethal capability is essential for responding to these threats. The thesis' methodology produces a short list of suitable non-lethal crowd control weapons for deployment in NEOs. Finally, the arguments for non-lethality in NEOs can be extended to other operations other than war, thus increasing the utility of non- lethal weapons in the U.S. military inventory.http://archive.org/details/nonlethalweapons1094513445U.S. Air Force (U.S.A.F.) author.Approved for public release; distribution is unlimited

Incentive design for adaptive agents

We consider a setting in which a principal seeks to induce an adaptive agent to select a target action by providing incentives on one or more actions. The agent maintains a belief about the value for each action—which may update based on experience—and selects at each time step the action with the maximal sum of value and associated incentive. The principal observes the agent’s selection, but has no information about the agent’s current beliefs or belief update process. For inducing the target action as soon as possible, or as often as possible over a fixed time period, it is optimal for a principal with a per-period budget to assign the budget to the target action and wait for the agent to want to make that choice. But with an across-period budget, no algorithm can provide good performance on all instance