Development of Prognosis in Palliative care Study (PiPS) predictor models to improve prognostication in advanced cancer: prospective cohort study

OBJECTIVE: To develop a novel prognostic indicator for use in patients with advanced cancer that is significantly better than clinicians' estimates of survival. DESIGN: Prospective multicentre observational cohort study. SETTING: 18 palliative care services in the UK (including hospices, hospital support teams, and community teams). PARTICIPANTS: 1018 patients with locally advanced or metastatic cancer, no longer being treated for cancer, and recently referred to palliative care services. MAIN OUTCOME MEASURES: Performance of a composite model to predict whether patients were likely to survive for "days" (0-13 days), "weeks" (14-55 days), or "months+" (>55 days), compared with actual survival and clinicians' predictions. RESULTS: On multivariate analysis, 11 core variables (pulse rate, general health status, mental test score, performance status, presence of anorexia, presence of any site of metastatic disease, presence of liver metastases, C reactive protein, white blood count, platelet count, and urea) independently predicted both two week and two month survival. Four variables had prognostic significance only for two week survival (dyspnoea, dysphagia, bone metastases, and alanine transaminase), and eight variables had prognostic significance only for two month survival (primary breast cancer, male genital cancer, tiredness, loss of weight, lymphocyte count, neutrophil count, alkaline phosphatase, and albumin). Separate prognostic models were created for patients without (PiPS-A) or with (PiPS-B) blood results. The area under the curve for all models varied between 0.79 and 0.86. Absolute agreement between actual survival and PiPS predictions was 57.3% (after correction for over-optimism). The median survival across the PiPS-A categories was 5, 33, and 92 days and survival across PiPS-B categories was 7, 32, and 100.5 days. All models performed as well as, or better than, clinicians' estimates of survival. CONCLUSIONS: In patients with advanced cancer no longer being treated, a combination of clinical and laboratory variables can reliably predict two week and two month survival

Simple threshold rules solve explore/exploit trade‐offs in a resource accumulation search task

How, and how well, do people switch between exploration and exploitation to search for and accumulate resources? We study the decision processes underlying such exploration/exploitation trade‐offs using a novel card selection task that captures the common situation of searching among multiple resources (e.g., jobs) that can be exploited without depleting. With experience, participants learn to switch appropriately between exploration and exploitation and approach optimal performance. We model participants' behavior on this task with random, threshold, and sampling strategies, and find that a linear decreasing threshold rule best fits participants' results. Further evidence that participants use decreasing threshold‐based strategies comes from reaction time differences between exploration and exploitation; however, participants themselves report non‐decreasing thresholds. Decreasing threshold strategies that “front‐load” exploration and switch quickly to exploitation are particularly effective in resource accumulation tasks, in contrast to optimal stopping problems like the Secretary Problem requiring longer exploration

Field Days and Farm Tours and 2001 Growing Season

Includes: Field Days and Farm Tours 2001 Growing Seaso

Resistance of Kansas Sclerotinia homoeocarpa isolates to thiophanate-methyl and determination of associated β-tubulin mutation

Citation: Ostrander, J., Todd, R., & Kennelly, M. (2014). Resistance of Kansas Sclerotinia homoeocarpa Isolates to Thiophanate-Methyl and Determination of Associated β-Tubulin Mutation. Plant Health Progress, 15(2), 23-27. https://doi.org/10.1094/PHP-RS-13-0120.Eighty-two isolates of Sclerotinia homoeocarpa from 12 sites in Kansas were evaluated for in vitro sensitivity to the methyl benzimidazole carbamate (MBC) fungicide thiophanate-methyl at the discriminatory dose of 10 μg/ml. Seventeen isolates were sensitive to thiophanate-methyl and the remaining isolates were resistant. Of the 65 isolates from golf course putting greens, two isolates were sensitive and the remaining 63 isolates were resistant. Six resistant and five sensitive isolates were also evaluated in greenhouse assays on fungicide-treated plants. The isolates that were sensitive to thiophanate-methyl in vitro did not cause any disease on thiophanate-methyl-treated plants, and those that were resistant in vitro caused blighting on treated plants equivalent to the nontreated controls. The entire β-tubulin gene was sequenced for four resistant and four sensitive isolates. The resistant isolates all harbored a substitution of alanine for glutamic acid at codon 198 (E198A). These results provide a starting point for further surveys and monitoring of fungicide sensitivity

Identifying prognostic structural features in tissue sections of colon cancer patients using point pattern analysis

Diagnosis and prognosis of cancer is informed by the architecture inherent in cancer patient tissue sections. This architecture is typically identified by pathologists, yet advances in computational image analysis facilitate quantitative assessment of this structure. In this article we develop a spatial point process approach in order to describe patterns in cell distribution within tissue samples taken from colorectal cancer (CRC) patients. In particular, our approach is centered on the Palm intensity function. This leads to taking an approximate-likelihood technique in fitting point processes models. We consider two Neyman-Scott point processes and a void process, fitting these point process models to the CRC patient data. We find that the parameter estimates of these models may be used to quantify the spatial arrangement of cells. Importantly, we observe characteristic differences in the spatial arrangement of cells between patients who died from CRC and those alive at follow-up