The objective of this review is to provide an update on prognostication in patients with advanced cancer, and to discuss future directions for research in this field. Accurate prognostication of survival for patients with advanced cancer is vital, as patient life expectancy informs many important personal and clinical decisions. The most common prognostic approach is clinician prediction of survival (CPS) using temporal, surprise, or probabilistic questions. The surprise and probabilistic questions may be more accurate than the temporal approach, partly by limiting the time frame of prediction. Prognostic models such as the Glasgow Prognostic Score (GPS), Palliative Performance Scale (PPS), Palliative Prognostic Score (PaP), Palliative Prognostic Index (PPI), or Prognosis in Palliative Care Study (PiPS) predictor model may augment CPS. However, care must be taken to select the appropriate tool since prognostic accuracy varies by patient population, setting, and time frame of prediction. In addition to life expectancy, patients and caregivers often desire that expected treatment outcomes and bodily changes be communicated to them in a sensible manner at an appropriate time. We propose the following 10 major themes for future prognostication research: 1) enhancing prognostic accuracy; 2) improving reliability and reproducibility of prognosis; 3) identifying the appropriate prognostic tool for a given setting; 4) predicting the risks and benefits of cancer therapies; 5) predicting survival for pediatric

Enteral and parenteral nutrition in cancer patients, a comparison of complication rates: an updated systematic review and (cumulative) meta-analysis Chow

Background Research on cannabis use among those with a history of cancer is limited. Methods Prevalence of past‐year cannabis use among individuals with and without a cancer history and predictors of use within these 2 groups were determined using data from the Population Assessment of Tobacco and Health study, a nationally representative, longitudinal survey conducted in the United States (waves 1‐4; 2013‐2018). Discrete time survival analyses were used to estimate baseline (wave 1) predictors (physical health status, mental health status, pain, and demographic variables) on past‐year engagement with cannabis within individuals who reported a cancer diagnosis at wave 1 (n = 1022) and individuals who reported never having cancer at any wave (n = 19,702). Results At the most recent survey, 8% of cancer survivors reported past‐year cannabis use, compared with 15% of those without a cancer history. Across 4 time points, an estimated 3.8% of cancer survivors engaged with cannabis, as compared to 6.5% of those without a cancer history. Across both groups, older age and having health insurance were associated with lower likelihood of engaging in cannabis use, whereas greater levels of pain were associated with higher likelihood of engaging in cannabis use. Among those without a cancer history, being female, White, and having better mental health status were associated with lower likelihood of engaging in cannabis use. Conclusions Although cannabis use prevalence is lower among cancer survivors, the reasons for use are not markedly different from those without a cancer history. Continued monitoring of use, reasons for use, and harms or benefits is warranted. Lay Summary Results from this study, which uses data from the Population Assessment of Tobacco and Health Study, indicate that cannabis use is generally increasing across cancer survivors and those without a history of cancer. Cancer survivors are using cannabis at slightly lower rates than those without a history of cancer. Factors related to pain seem to be more prevalent in cancer populations relative to the general population, and could be contributing to cannabis use within cancer survivor populations.

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