78 research outputs found
sj-pdf-1-smm-10.1177_09622802221142529 - Supplemental material for Test sensitivity in a prospective cancer screening program: A critique of a common proxy measure
No full textSupplemental material, sj-pdf-1-smm-10.1177_09622802221142529 for Test sensitivity in a prospective cancer screening program: A critique of a common proxy measure by Jane Lange, Yibai Zhao, Kemal Caglar Gogebakan, Antonio Olivas-Martinez, Marc D. Ryser, Charlotte C. Gard and Ruth Etzioni in Statistical Methods in Medical Research</p
Thermal quantum electrodynamics of nonrelativistic charged fluids
No full textThe theory relevant to the study of matter in equilibrium with the radiation field is thermal quantum electrodynamics (TQED). We present a formulation of the theory, suitable for nonrelativistic fluids, based on a joint functional integral representation of matter and field variables. In this formalism cluster expansion techniques of classical statistical mechanics become operative. They provide an alternative to the usual Feynman diagrammatics in many-body problems, which is not perturbative with respect to the coupling constant. As an application we show that the effective Coulomb interaction between quantum charges is partially screened by thermalized photons at large distances. More precisely one observes an exact cancellation of the dipolar electric part of the interaction, so that the asymptotic particle density correlation is now determined by relativistic effects. It still has the r−6 decay typical for quantum charges, but with an amplitude strongly reduced by a relativistic factor
Triviality of the 2D stochastic Allen-Cahn equation
No full textWe consider the stochastic Allen-Cahn equation driven by mollified space-time white noise. We show that, as the mollifier is removed, the solutions converge weakly to
0, independently of the initial condition. If the intensity of the noise simultaneously converges to 0 at a sufficiently fast rate, then the solutions converge to those of the
deterministic equation. At the critical rate, the limiting solution is still deterministic, but it exhibits an additional damping term
Outcomes of Active Surveillance for Ductal Carcinoma in Situ: A Computational Risk Analysis.
No full textBACKGROUND
Ductal carcinoma in situ (DCIS) is a noninvasive breast lesion with uncertain risk for invasive progression. Usual care (UC) for DCIS consists of treatment upon diagnosis, thus potentially overtreating patients with low propensity for progression. One strategy to reduce overtreatment is active surveillance (AS), whereby DCIS is treated only upon detection of invasive disease. Our goal was to perform a quantitative evaluation of outcomes following an AS strategy for DCIS.
METHODS
Age-stratified, 10-year disease-specific cumulative mortality (DSCM) for AS was calculated using a computational risk projection model based upon published estimates for natural history parameters, and Surveillance, Epidemiology, and End Results data for outcomes. AS projections were compared with the DSCM for patients who received UC. To quantify the propagation of parameter uncertainty, a 95% projection range (PR) was computed, and sensitivity analyses were performed.
RESULTS
Under the assumption that AS cannot outperform UC, the projected median differences in 10-year DSCM between AS and UC when diagnosed at ages 40, 55, and 70 years were 2.6% (PR = 1.4%-5.1%), 1.5% (PR = 0.5%-3.5%), and 0.6% (PR = 0.0%-2.4), respectively. Corresponding median numbers of patients needed to treat to avert one breast cancer death were 38.3 (PR = 19.7-69.9), 67.3 (PR = 28.7-211.4), and 157.2 (PR = 41.1-3872.8), respectively. Sensitivity analyses showed that the parameter with greatest impact on DSCM was the probability of understaging invasive cancer at diagnosis.
CONCLUSION
AS could be a viable management strategy for carefully selected DCIS patients, particularly among older age groups and those with substantial competing mortality risks. The effectiveness of AS could be markedly improved by reducing the rate of understaging
Evolutionary measures show that recurrence of DCIS is distinct from progression to breast cancer
No full textAbstract Background Progression from pre-cancers like ductal carcinoma in situ (DCIS) to invasive disease (cancer) is driven by somatic evolution and is altered by clinical interventions. We hypothesized that genetic and/or phenotypic intra-tumor heterogeneity would predict clinical outcomes for DCIS since it serves as the substrate for natural selection among cells. Methods We profiled two samples from two geographically distinct foci from each DCIS in both cross-sectional (n = 119) and longitudinal cohorts (n = 224), with whole exome sequencing, low-pass whole genome sequencing, and a panel of immunohistochemical markers. Results In the longitudinal cohorts, the only statistically significant associations with time to non-invasive DCIS recurrence were the combination of treatment (lumpectomy only vs mastectomy or lumpectomy with radiation, HR 12.13, p = 0.003, Wald test with FDR correction), ER status (HR 0.16 for ER+ compared to ER−, p = 0.0045), and divergence in SNVs between the two samples (HR 1.33 per 10% divergence, p = 0.018). SNV divergence also distinguished between pure DCIS and DCIS synchronous with invasive disease in the cross-sectional cohort. In contrast, the only statistically significant associations with time to progression to invasive disease were the combination of the width of the surgical margin (HR 0.67 per mm, p = 0.043) and the number of mutations that were detectable at high allele frequencies (HR 1.30 per 10 SNVs, p = 0.02). No predictors were significantly associated with both DCIS recurrence and progression to invasive disease, suggesting that the evolutionary scenarios that lead to these clinical outcomes are markedly different. Conclusions These results imply that recurrence with DCIS is a clinical and biological process different from invasive progression
Modeling of US Human Papillomavirus (HPV) Seroprevalence by Age and Sexual Behavior Indicates an Increasing Trend of HPV Infection Following the Sexual Revolution.
No full textBefore main banks : a selective historical overview of Japan's prewar financialsystem
No full textThe postwar experience of the Japanese banking system has received considerable attention recently partly because conditions in defeated Japan in 1945 (including high inflation and the need to switch from a military to a civilian economy) are similar to those in transition economies today. Policymakers in transition economies can learn a good deal from the experiences of Japan's postwar financial system but should remember that Japan also experienced extraordinary industrial growth and financial institution building in the late nineteenth and early twentieth centuries. Lessons to be learned from that experience include the following: Business conglomerates that did not continue to depend on government patronage were more successful than others in making the transition to a modern industrial economy. Banks that made a conscious effort to reduce their dependence on central bank credit were more successful than those that did not. The establishment of procedures for punishing defaulting borrowers helped the development of the payments system. Limits on the amount of lending to related parties appear to have contributed to financial stability (and could have contributed more if the newer"zaibatsu"had been as prudent as the older ones). Bank bailouts without accompanying reform (such as those the Bank of Japan undertook in 1920 and 1922) probably increased the likelihood of a more serious crisis, such as that of 1927. Capital standards - the minimum capital requirements established in the 1927 law - were a viable means of encouraging bank consolidation and more prudent lending. The public financial system served as a buffer when the banking sector was downsized.Banks&Banking Reform,Payment Systems&Infrastructure,Financial Intermediation,Financial Crisis Management&Restructuring,Decentralization,Financial Intermediation,Financial Crisis Management&Restructuring,Municipal Financial Management,Banking Law,Banks&Banking Reform
Multifocality and recurrence risk: a quantitative model of field cancerization
No full textPrimary tumors often emerge within genetically altered fields of premalignant cells that appear histologically normal but have a high chance of progression to malig-nancy. Clinical observations have suggested that these premalignant fields pose high risks for emergence of recurrent tumors if left behind after surgical removal of the pri-mary tumor. In this work, we develop a spatio-temporal stochastic model of epithelial carcinogenesis, combining cellular dynamics with a general framework for multi-stage genetic progression to cancer. Using the model, we investigate how various properties of the premalignant fields depend on microscopic cellular properties of the tissue. In particular, we provide analytic results for the size-distribution of the histologically un-detectable premalignant fields at the time of diagnosis, and investigate how the extent and geometry of these fields depend upon key groups of parameters associated with the tissue and genetic pathways. We also derive analytical results for the relative risks of local vs distant secondary tumors for different parameter regimes, a critical aspect for the optimal choice of post-operative therapy in carcinoma patients. This study contributes to a growing literature seeking to obtain a quantitative understanding of the spatial dynamics in cancer initiation.
Triviality of the 2D stochastic Allen-Cahn equation
No full textWe consider the stochastic Allen-Cahn equation driven by mollified space-time white noise. We show that, as the mollifier is removed, the solutions converge weakly to 0, independently of the initial condition. If the intensity of the noise simultaneously converges to 0 at a sufficiently fast rate, then the solutions converge to those of the deterministic equation. At the critical rate, the limiting solution is still deterministic, but it exhibits an additional damping term.PROPD
Mechanistic mathematical models: An underused platform for HPV research
No full textHealth economic modeling has become an invaluable methodology for the design and evaluation of clinical and public health interventions against the human papillomavirus (HPV) and associated diseases. At the same time, relatively little attention has been paid to a different yet complementary class of models, namely that of mechanistic mathematical models. The primary focus of mechanistic mathematical models is to better understand the intricate biologic mechanisms and dynamics of disease. Inspired by a long and successful history of mechanistic modeling in other biomedical fields, we highlight several areas of HPV research where mechanistic models have the potential to advance the field. We argue that by building quantitative bridges between biologic mechanism and population level data, mechanistic mathematical models provide a unique platform to enable collaborations between experimentalists who collect data at different physical scales of the HPV infection process. Through such collaborations, mechanistic mathematical models can accelerate and enhance the investigation of HPV and related diseases
- …
