Noblesse oblige? Determinants of survival in a life and death situation

This paper explores what determines the survival of people in a life–and-death situation. The sinking of the Titanic allows us to inquire whether pro-social behavior matters in such extreme situations. This event can be considered a quasi-natural experiment. The empirical results suggest that social norms such as ‘women and children first’ are persevered during such an event. Women of reproductive age and crew members had a higher probability of survival. Passenger class, fitness, group size, and cultural background also mattered.

Change Point Estimation in Monitoring Survival Time

Precise identification of the time when a change in a hospital outcome has occurred enables clinical experts to search for a potential special cause more effectively. In this paper, we develop change point estimation methods for survival time of a clinical procedure in the presence of patient mix in a Bayesian framework. We apply Bayesian hierarchical models to formulate the change point where there exists a step change in the mean survival time of patients who underwent cardiac surgery. The data are right censored since the monitoring is conducted over a limited follow-up period. We capture the effect of risk factors prior to the surgery using a Weibull accelerated failure time regression model. Markov Chain Monte Carlo is used to obtain posterior distributions of the change point parameters including location and magnitude of changes and also corresponding probabilistic intervals and inferences. The performance of the Bayesian estimator is investigated through simulations and the result shows that precise estimates can be obtained when they are used in conjunction with the risk-adjusted survival time CUSUM control charts for different magnitude scenarios. The proposed estimator shows a better performance where a longer follow-up period, censoring time, is applied. In comparison with the alternative built-in CUSUM estimator, more accurate and precise estimates are obtained by the Bayesian estimator. These superiorities are enhanced when probability quantification, flexibility and generalizability of the Bayesian change point detection model are also considered.

Modelling survival data to account for model uncertainty: a single model or model averaging?

This study considered the problem of predicting survival, based on three alternative models: a single Weibull, a mixture of Weibulls and a cure model. Instead of the common procedure of choosing a single “best” model, where “best” is defined in terms of goodness of fit to the data, a Bayesian model averaging (BMA) approach was adopted to account for model uncertainty. This was illustrated using a case study in which the aim was the description of lymphoma cancer survival with covariates given by phenotypes and gene expression. The results of this study indicate that if the sample size is sufficiently large, one of the three models emerge as having highest probability given the data, as indicated by the goodness of fit measure; the Bayesian information criterion (BIC). However, when the sample size was reduced, no single model was revealed as “best”, suggesting that a BMA approach would be appropriate. Although a BMA approach can compromise on goodness of fit to the data (when compared to the true model), it can provide robust predictions and facilitate more detailed investigation of the relationships between gene expression and patient survival. Keywords: Bayesian modelling; Bayesian model averaging; Cure model; Markov Chain Monte Carlo; Mixture model; Survival analysis; Weibull distribution

PRMT2 and RORγ expression are associated with breast cancer survival outcomes

Protein arginine methyltransferases (PRMTs) methylate arginine residues on histones and target transcription factors that play critical roles in many cellular processes, including gene transcription, mRNA splicing, proliferation, and differentiation. Recent studies have linked PRMT-dependent epigenetic marks and modifications to carcinogenesis and metastasis in cancer. However, the role of PRMT2-dependent signaling in breast cancer remains obscure. We demonstrate PRMT2 mRNA expression was significantly decreased in breast cancer relative to normal breast. Gene expression profiling, Ingenuity and protein-protein interaction network analysis after PRMT2-short interfering RNA transfection into MCF-7 cells, revealed that PRMT2-dependent gene expression is involved in cell-cycle regulation and checkpoint control, chromosomal instability, DNA repair, and carcinogenesis. For example, PRMT2 depletion achieved the following: 1) increased p21 and decreased cyclinD1 expression in (several) breast cancer cell lines, 2) decreased cell migration, 3) induced an increase in nucleotide excision repair and homologous recombination DNA repair, and 4) increased the probability of distance metastasis free survival (DMFS). The expression of PRMT2 and retinoid-related orphan receptor-γ (RORγ) is inversely correlated in estrogen receptor-positive breast cancer and increased RORγ expression increases DMFS. Furthermore, we found decreased expression of the PRMT2-dependent signature is significantly associated with increased probability of DMFS. Finally, weighted gene coexpression network analysis demonstrated a significant correlation between PRMT2-dependent genes and cell-cycle checkpoint, kinetochore, and DNA repair circuits. Strikingly, these PRMT2-dependent circuits are correlated with pan-cancer metagene signatures associated with epithelial-mesenchymal transition and chromosomal instability. This study demonstrates the role and significant correlation between a histone methyltransferase (PRMT2)-dependent signature, RORγ, the cell-cycle regulation, DNA repair circuits, and breast cancer survival outcomes.

Estimation of the time of a linear trend in monitoring survival time

Change point estimation is recognized as an essential tool of root cause analyses within quality control programs as it enables clinical experts to search for potential causes of change in hospital outcomes more effectively. In this paper, we consider estimation of the time when a linear trend disturbance has occurred in survival time following an in-control clinical intervention in the presence of variable patient mix. To model the process and change point, a linear trend in the survival time of patients who underwent cardiac surgery is formulated using hierarchical models in a Bayesian framework. The data are right censored since the monitoring is conducted over a limited follow-up period. We capture the effect of risk factors prior to the surgery using a Weibull accelerated failure time regression model. We use Markov Chain Monte Carlo to obtain posterior distributions of the change point parameters including the location and the slope size of the trend and also corresponding probabilistic intervals and inferences. The performance of the Bayesian estimator is investigated through simulations and the result shows that precise estimates can be obtained when they are used in conjunction with the risk-adjusted survival time cumulative sum control chart (CUSUM) control charts for different trend scenarios. In comparison with the alternatives, step change point model and built-in CUSUM estimator, more accurate and precise estimates are obtained by the proposed Bayesian estimator over linear trends. These superiorities are enhanced when probability quantification, flexibility and generalizability of the Bayesian change point detection model are also considered.

Assessing the effects of line capture and barotrauma relief procedures on post-release survival of key tropical reef fish species in Australia using recreational tagging clubs.

Common coral trout, Plectropomus leopardus Lacepede, crimson snapper, Lutjanus erythropterus Bloch, saddletail snapper, Lutjanus malabaricus (Bloch & Schneider), red emperor, Lutjanus sebae (Cuvier), redthroat emperor, Lethrinus miniatus (Schneider) and grass emperor, Lethrinus laticaudis Alleyne & Macleay, were tagged to determine the effects of barotrauma relief procedures (weighted shot-line release and venting using a hollow needle) and other factors on survival. Release condition was the most significant factor affecting the subsequent recapture rate of all species. Capture depth was significant in all species apart from L. malabaricus and L. miniatus, the general trend being reduced recapture probability with increasing capture depth. Recapture rates of fish hooked in either the lip or mouth were generally significantly higher than for those hooked in the throat or gut. Statistically significant benefit from treating fish for barotrauma was found in only L. malabaricus, but the lack of any negative effects of treating fish indicated that the practices of venting and shot-lining should not be discouraged by fisheries managers for these species.

A boat hitchhiker's guide to survival: Cabomba caroliniana desiccation resistance and survival ability

Cabomba caroliniana is a submersed macrophyte that has become a serious invader. Cabomba predominantly spreads by stem fragments, in particular through unintentional transport on boat trailers ('hitch hiking'). Desiccation resistance affects the potential dispersal radius. Therefore, knowledge of maximum survival times allows predicting future dispersal. Experiments were conducted to assess desiccation resistance and survival ability of cabomba fragments under various environmental scenarios. Cabomba fragments were highly tolerant of desiccation. However, even relatively low wind speeds resulted in rapid mass loss, indicating a low survival rate of fragments exposed to air currents, such as fragments transported on a boat trailer. The experiments indicated that cabomba could survive at least 3 h of overland transport if exposed to wind. However, even small clumps of cabomba could potentially survive up to 42 h. Thus, targeting the transport of clumps of macrophytes should receive high priority in management. The high resilience of cabomba to desiccation demonstrates the risk of continuing spread. Because of the high probability of fragment viability on arrival, preventing fragment uptake on boat trailers is paramount to reduce the risk of further spread. These findings will assist improving models that predict the spread of aquatic invasive macrophytes.

A boat hitchhiker’s guide to survival: Cabomba caroliniana desiccation resistance and survival ability

Cabomba caroliniana is a submersed macrophyte that has become a serious invader. Cabomba predominantly spreads by stem fragments, in particular through unintentional transport on boat trailers (‘hitch hiking’). Desiccation resistance affects the potential dispersal radius. Therefore, knowledge of maximum survival times allows predicting future dispersal. Experiments were conducted to assess desiccation resistance and survival ability of cabomba fragments under various environmental scenarios. Cabomba fragments were highly tolerant of desiccation. However, even relatively low wind speeds resulted in rapid mass loss, indicating a low survival rate of fragments exposed to air currents, such as fragments transported on a boat trailer. The experiments indicated that cabomba could survive at least 3 h of overland transport if exposed to wind. However, even small clumps of cabomba could potentially survive up to 42 h. Thus, targeting the transport of clumps of macrophytes should receive high priority in management. The high resilience of cabomba to desiccation demonstrates the risk of continuing spread. Because of the high probability of fragment viability on arrival, preventing fragment uptake on boat trailers is paramount to reduce the risk of further spread. These findings will assist improving models that predict the spread of aquatic invasive macrophytes.

Modelling initial survival and growth of radiata pine in New Zealand.

A sensitive framework has been developed for modelling young radiata pine survival, its growth and its size class distribution, from time of planting to age 5 or 6 years. The data and analysis refer to the Central North Island region of New Zealand. The survival function is derived from a Weibull probability density function, to reflect diminishing mortality with the passage of time in young stands. An anamorphic family of trends was used, as very little between-tree competition can be expected in young stands. An exponential height function was found to fit best the lower portion of its sigmoid form. The most appropriate basal area/ha exponential function included an allometric adjustment which resulted in compatible mean height and basal area/ha models. Each of these equations successfully represented the effects of several establishment practices by making coefficients linear functions of site factors, management activities and their interactions. Height and diameter distribution modelling techniques that ensured compatibility with stand values were employed to represent the effects of management practices on crop variation. Model parameters for this research were estimated using data from site preparation experiments in the region and were tested with some independent data sets.

Large rapidity gaps survival probabilities at LHC

We calculate the probability of large rapidity gaps in high energy hadronic collisions using a model based on QCD mini-jets and soft gluon emission down into the infrared region. Comparing with other models we find a remarkable agreement among most predictions.

How Does Effectual Logic Impact Survival of High-tech Startups in an Emerging Economy? - Evidence from 99tests.com Case Study

During the early stages of operation, high-tech startups need to overcome the liability of newness and manage high degree of uncertainty. Several high-tech startups fail due to inability to deal with skeptical customers, underdeveloped markets and limited resources in selling an offering that has no precedent. This paper leverages the principles of effectuation (a logic of entrepreneurial decision making under uncertainty) to explain the journey from creation to survival of high-tech startups in an emerging economy. Based on the 99tests.com case study, this paper suggests that early stage high-tech startups in emerging economies can increase their probability of survival by adopting the principles of effectuation.

Survival and Growth of American Alligator (Alligator mississippiensis) hatchlings after artificial incubation and repatriation

Hatchling American Alligators (Alligator mississippiensis) produced from artificially incubated wild eggs were returned to their natal areas (repatriated). We compared artificially incubated and repatriated hatchlings released within and outside the maternal alligator’s home range with naturally incubated hatchlings captured and released within the maternal alligator’s home range on Lake Apopka, Lake Griffin, and Orange Lake in Florida. We used probability of recapture and total length at approximately nine months after hatching as indices of survival and growth rates. Artificially incubated hatchlings released outside of the maternal alligator’s home range had lower recapture probabilities than either naturally incubated hatchlings or artificially incubated hatchlings released near the original nest site. Recapture probabilities of other treatments did not differ significantly. Artificially incubated hatchlings were approximately 6% shorter than naturally incubated hatchlings at approximately nine months after hatching. We concluded that repatriation of hatchlings probably would not have long-term effects on populations because of the resiliency of alligator populations to alterations of early age-class survival and growth rates of the magnitude that we observed. Repatriation of hatchlings may be an economical alternative to repatriation of older juveniles for population restoration. However, the location of release may affect subsequent survival and growth.

Survival expectations of the obese: Is excess mortality reflected in perceptions?

OBJECTIVE: This study compared self-reported subjective life expectancy (i.e., probability of living to age 75) for normal-weight, overweight, and obese weight groups to examine whether individuals are internalizing information about the health risks due to excessive weight. RESEARCH METHODS AND PROCEDURES: Using data from the Health and Retirement Study, a total of 9035 individuals 51 to 61 years old were analyzed by BMI category. The primary outcome measure was individuals' reports about their own expectations of survival to age 75. Absolute and relative risks of survival were compared with published estimates of survival to age 75. RESULTS: Consistently, higher levels of BMI were associated with lower self-estimated survival probabilities. Differences relative to normal weight ranged from 4.9% (p < 0.01) for male nonsmokers to 8.8% (p < 0.001) for female nonsmokers. However, these differences were substantially less than those obtained from published survival curve estimates, suggesting that obese individuals tended to underestimate mortality risks. DISCUSSION: Individuals appeared to underestimate the mortality risks of excessive weight; thus, knowledge campaigns about the risks of obesity should remain a top priority.

Functional Variants in Notch Pathway Genes NCOR2, NCSTN, and MAML2 Predict Survival of Patients with Cutaneous Melanoma.

BACKGROUND: The Notch signaling pathway is constitutively activated in human cutaneous melanoma to promote growth and aggressive metastatic potential of primary melanoma cells. Therefore, genetic variants in Notch pathway genes may affect the prognosis of cutaneous melanoma patients. METHODS: We identified 6,256 SNPs in 48 Notch genes in 858 cutaneous melanoma patients included in a previously published cutaneous melanoma genome-wide association study dataset. Multivariate and stepwise Cox proportional hazards regression and false-positive report probability corrections were performed to evaluate associations between putative functional SNPs and cutaneous melanoma disease-specific survival. Receiver operating characteristic curve was constructed, and area under the curve was used to assess the classification performance of the model. RESULTS: Four putative functional SNPs of Notch pathway genes had independent and joint predictive roles in survival of cutaneous melanoma patients. The most significant variant was NCOR2 rs2342924 T>C (adjusted HR, 2.71; 95% confidence interval, 1.73-4.23; Ptrend = 9.62 × 10(-7)), followed by NCSTN rs1124379 G>A, NCOR2 rs10846684 G>A, and MAML2 rs7953425 G>A (Ptrend = 0.005, 0.005, and 0.013, respectively). The receiver operating characteristic analysis revealed that area under the curve was significantly increased after adding the combined unfavorable genotype score to the model containing the known clinicopathologic factors. CONCLUSIONS: Our results suggest that SNPs in Notch pathway genes may be predictors of cutaneous melanoma disease-specific survival. IMPACT: Our discovery offers a translational potential for using genetic variants in Notch pathway genes as a genotype score of biomarkers for developing an improved prognostic assessment and personalized management of cutaneous melanoma patients.

Linear quadratic and tumour control probability modelling in external beam radiotherapy

The standard linear-quadratic (LQ) survival model for external beam radiotherapy is reviewed with particular emphasis on studying how different schedules of radiation treatment planning may be affected by different tumour repopulation kinetics. The LQ model is further examined in the context of tumour control probability (TCP) models. The application of the Zaider and Minerbo non-Poissonian TCP model incorporating the effect of cellular repopulation is reviewed. In particular the recent development of a cell cycle model within the original Zaider and Minerbo TCP formalism is highlighted. Application of this TCP cell-cycle model in clinical treatment plans is explored and analysed.