Did quality of life for older cancer survivors improve with the turn of the century in the United States?

ObjectivesAlthough survival after a cancer diagnosis has improved considerably over the past 20 years, little is known about trends in health-related quality-of-life (HRQOL) for older prostate, breast, and lung cancer survivors.MethodsUsing a population-based registry with longitudinal patient reported outcomes (the National Cancer Institute Surveillance, Epidemiology and End Results database linked to Medicare Health Outcomes Survey), we analyzed Medicare Advantage patients diagnosed with cancer during 1998–2011, who completed surveys regarding HRQOL through 2013. ‘Early Era’ patients were treated during 1998–2003; ‘Late Era’ patients were treated during 2006–2011. After propensity score matching, post-diagnosis changes in health utility (HU), Physical Component Summary (PCS) and Mental Component Summary (MCS) scores were calculated and compared between the two eras.ResultWe identified 208 older patients with prostate, 276 with breast and 76 with lung cancer who were treated in the ‘Early Era’ and matched to equal numbers in the ‘Late Era’. Mean age of patients in early and late era was 72 and 73 years, respectively. The mean post-diagnosis decline in health utility for patients treated in the ‘Late Era’ was not significantly different from the ‘Early Era’ for any cancer (Prostate [early vs. late]: ?0.06 vs. -0.03, p = .09; Breast: ?0.03 vs. ?0.04, p = .65; Lung: ?0.07 vs. ?0.07, p = .95); nor for Physical Component Summary or Mental Component Summary scores.ConclusionOlder patients treated for prostate, breast or lung cancer in the later era reported similar outcomes of changes in HRQOL compared to earlier era patients.     

A literature-based treatment algorithm for low-grade neuroendocrine liver metastases

BackgroundThe optimal timing of treatment of liver metastases from low-grade neuroendocrine tumors (LG-NELM) varies significantly due to numerous treatment modalities and the literature supporting various treatment(s). This study sought to create and validate a literature-based treatment algorithm for LG-NELM.MethodsA treatment algorithm to maximize overall survival (OS) was designed using peer-reviewed articles evaluating treatment of LG-NELM. This algorithm was retrospectively applied to patients treated for LG-NELM at our institution. Deviation was determined based on whether or not a patient received treatment consistent with that recommended by the algorithm. Patients who did and did not deviate from the algorithm were compared with respect to OS and number of treatments.ResultsApplying our algorithm to a 149-patient cohort, 57 (38%) deviated from recommended treatment. Deviation occurred in the form of alternative (28, 49%) versus additional procedures (29, 51%). Algorithm deviators underwent significantly more procedures than non-deviators (median 1 vs. 2, p < 0.001). Cox model indicated no difference in OS associated with algorithm deviation (HR 1.19, p = 0.58) when controlling for age and tumor characteristics.ConclusionThis literature-based algorithm helps standardize treatment protocols in patients with LG-NELM and can reduce cost and risk by minimizing unnecessary procedures. Prospective implementation and validation is required.     

EAU-EANM-ESTRO-ESUR-SIOG Guidelines on Prostate Cancer—2020 Update. Part 1: Screening,Diagnosis, and Local Treatment with Curative Intent

ObjectiveTo present a summary of the 2020 version of the European Association of Urology (EAU)-European Association of Nuclear Medicine (EANM)-European Society for Radiotherapy and Oncology (ESTRO)-European Society of Urogenital Radiology (ESUR)-International Society of Geriatric Oncology (SIOG) guidelines on screening, diagnosis, and local treatment of clinically localised prostate cancer (PCa).Evidence acquisitionThe panel performed a literature review of new data, covering the time frame between 2016 and 2020. The guidelines were updated and a strength rating for each recommendation was added based on a systematic review of the evidence.Evidence synthesisA risk-adapted strategy for identifying men who may develop PCa is advised, generally commencing at 50 yr of age and based on individualised life expectancy. Risk-adapted screening should be offered to men at increased risk from the age of 45 yr and to breast cancer susceptibility gene (BRCA) mutation carriers, who have been confirmed to be at risk of early and aggressive disease (mainly BRAC2), from around 40 yr of age. The use of multiparametric magnetic resonance imaging in order to avoid unnecessary biopsies is recommended. When a biopsy is performed, a combination of targeted and systematic biopsies must be offered. There is currently no place for the routine use of tissue-based biomarkers. Whilst prostate-specific membrane antigen positron emission tomography computed tomography is the most sensitive staging procedure, the lack of outcome benefit remains a major limitation. Active surveillance (AS) should always be discussed with low-risk patients, as well as with selected intermediate-risk patients with favourable International Society of Urological Pathology (ISUP) 2 lesions. Local therapies are addressed, as well as the AS journey and the management of persistent prostate-specific antigen after surgery. A strong recommendation to consider moderate hypofractionation in intermediate-risk patients is provided. Patients with cN1 PCa should be offered a local treatment combined with long-term hormonal treatment.ConclusionsThe evidence in the field of diagnosis, staging, and treatment of localised PCa is evolving rapidly. The 2020 EAU-EANM-ESTRO-ESUR-SIOG guidelines on PCa summarise the most recent findings and advice for their use in clinical practice. These PCa guidelines reflect the multidisciplinary nature of PCa management.Patient summaryUpdated prostate cancer guidelines are presented, addressing screening, diagnosis, and local treatment with curative intent. These guidelines rely on the available scientific evidence, and new insights will need to be considered and included on a regular basis. In some cases, the supporting evidence for new treatment options is not yet strong enough to provide a recommendation, which is why continuous updating is important. Patients must be fully informed of all relevant options and, together with their treating physicians, decide on the most optimal management for them.     

Validation of a test meal paradigm to experimentally manipulate meal-related fears: A registered report

Fear is central to conceptualizations of weight and shape-focused eating disorders. The current study will examine the reliability and validity of a test meal paradigm that varies perceptions of fat content to manipulate fear. Undergraduate women with elevated eating pathology (N = 96) will be randomized to one of three test meal conditions: two “low” fat yogurts, two “high” fat yogurts, or one “high” fat and one “low” fat yogurt. In actuality, all yogurts will have the same fat content. Supporting reliability, we hypothesize that self-reported fear and electrodermal activity (psychophysiological index of fear-related arousal) will exhibit good test–retest reliability over a 48-hr period in the “high” fat/“high” fat and “low” fat/“low” fat conditions. Supporting construct validity, self-reported fear and electrodermal activity will be elevated during the “high” versus “low” fat condition and responses to the “high" fat condition will correlate with fear of food, eating, and weight gain. Supporting discriminant validity, self-reported disgust and anger will be comparable in the “high” and “low” fat conditions and will exhibit weak correlations with trait measures of disgust and anger. This experimental paradigm will allow researchers to manipulate fear in order understand the mechanisms by which fear maintains eating pathology.     

Estimating Local Cellular Density in Glioma Using MR Imaging Data

BACKGROUND AND PURPOSE:Increased cellular density is a hallmark of gliomas, both in the bulk of the tumor and in areas of tumor infiltration into surrounding brain. Altered cellular density causes altered imaging findings, but the degree to which cellular density can be quantitatively estimated from imaging is unknown. The purpose of this study was to discover the best MR imaging and processing techniques to make quantitative and spatially specific estimates of cellular density.MATERIALS AND METHODS:We collected stereotactic biopsies in a prospective imaging clinical trial targeting untreated patients with gliomas at our institution undergoing their first resection. The data included preoperative MR imaging with conventional anatomic, diffusion, perfusion, and permeability sequences and quantitative histopathology on biopsy samples. We then used multiple machine learning methodologies to estimate cellular density using local intensity information from the MR images and quantitative cellular density measurements at the biopsy coordinates as the criterion standard.RESULTS:The random forest methodology estimated cellular density with R² = 0.59 between predicted and observed values using 4 input imaging sequences chosen from our full set of imaging data (T2, fractional anisotropy, CBF, and area under the curve from permeability imaging). Limiting input to conventional MR images (T1 pre- and postcontrast, T2, and FLAIR) yielded slightly degraded performance (R² = 0.52). Outputs were also reported as graphic maps.CONCLUSIONS:Cellular density can be estimated with moderate-to-strong correlations using MR imaging inputs. The random forest machine learning model provided the best estimates. These spatially specific estimates of cellular density will likely be useful in guiding both diagnosis and treatment.

Increased cellular density (CD) is a hallmark of cancer and a key feature in histologic glioma analysis.¹ Mapping cellular density throughout a tumor would be a valuable tool to probe how tumors infiltrate and analyze the transition between diseased and healthy brain. However, measuring CD requires tissue, which entails additional risks and is expensive to obtain. There is no currently accepted clinical algorithm to translate imaging data into quantitative assessments of CD.There is great need for a method to estimate CD noninvasively in human patients with gliomas. In this article, we describe the development of such a method using MR imaging data inputs by correlating with multiple biopsy specimens acquired during a prospective human clinical trial. We obtained comprehensive MR imaging, including conventional, diffusion, perfusion, and permeability imaging sequences. We used machine learning approaches to correlate imaging findings with CD measurements from pathology, devised an algorithm to estimate CD from MR imaging inputs, and generated CD maps for the visual display of the predictions. We identified the most informative imaging data subset. This work has multiple applications in the diagnosis and treatment of patients with gliomas: For example, the method can be used to guide biopsy, resection, and surgery and delineate tumor borderzones both pre- and postoperatively.²     

Time-varying prognostic value of primary tumor sidedness in metastatic colorectal cancer: A population-based study and meta-analysis

We studied the prognostic value of primary tumor sidedness in metastatic colorectal cancer over time and across treatment lines. Population data on synchronous metastatic colorectal cancer patients were extracted from the Netherlands Cancer Registry and SEER database. Pubmed, EMBASE and Cochrane library were searched for prospective studies on metastatic colorectal cancer to conduct a meta-analysis. Inclusion criteria consisted of metastatic disease, systemic treatment with palliative intent and specification of primary tumor location. Data were pooled using a random-effects model. For the population-based data, multivariable Cox models were constructed. The Grambsch-Therneau test was conducted to evaluate the potential time-varying nature of sidedness. Meta-regression incorporating treatment-line as variable was conducted to test the pre-specified hypothesis that the prognostic value of sidedness varies over time. Analysis of 12 885 and 16 160 synchronous metastatic colorectal cancer patients registered in the Netherlands Cancer Registry and SEER database, respectively, indicated a time-varying prognostic value of sidedness (P < .01). Thirty-one studies were selected for the meta-analysis (9558 patients for overall survival analysis). Pooled univariable hazard ratio_{left-sided/right-sided} for overall survival was 0.71 (95% CI: 0.65-0.76) in 1st-line, 0.76 (0.54-1.06) in 2nd-line and 1.01 (0.86-1.19) in 3rd-line studies. Hazard ratios were significantly influenced by treatment line (P = .035). The prognostic value of sidedness of the primary tumor in metastatic colorectal cancer patients treated with palliative systemic therapy decreases over time since diagnosis, suggesting that sidedness may not be a useful stratification factor in late-line trials. This decrease in prognostic value should be taken into account when providing prognostic information to patients.