Computational augmentation of neoplastic endometrial glands in digital pathology displays.

The pathologic diagnosis of neoplasia requires localization and classification of lesional tissue, a process that depends on the recognition of an abnormal spatial distribution of neoplastic elements relative to admixed normal background tissue. In endometrial intraepithelial neoplasia (EIN), a pre-cancer usually managed by hysterectomy, a clonally mutated proliferation of cytologically altered glands ('neoplastic-EIN') aggregates in clusters that also contain background non-neoplastic glands ('background-NL'). Here, we used image analysis to classify individual glands within endometrial tissue fragments as neoplastic-EIN or background-NL, and we used the distribution of predictions to localize foci diagnostic of EIN. Nuclear coordinates were automatically assigned and were used as vertices to generate Delaunay triangulations for each gland. Graph statistical variables were used to develop random forest algorithms to classify glands as neoplastic-EIN or background-NL. Individual glands in an independent validation set were scored by a 'ground truth' biomarker (PAX2 immunohistochemistry). We found that exclusion of small glands led to improvement in classification accuracy. Using an inclusion threshold of 200 nuclei per gland, our final model classification accuracy was 77.5% in the validation set, with a positive predictive value of 0.81. We leveraged this high positive predictive value in a point cloud overlay display to assist end-user identification of EIN foci. This study demonstrates that graph theory approaches applied to small-scale anatomic elements in the endometrium allow biologic classification by machine learning, and that spatial superimposition over large-scale tissue expanses can have practical diagnostic utility. We expect this augmented diagnostic approach to be generalizable to commonly encountered problems in other organ systems. © 2020 The Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

A New Classification of Benign, Premalignant, and Malignant Endometrial Tissues Using Machine Learning Applied to 1413 Candidate Variables.

Benign normal (NL), premalignant (endometrial intraepithelial neoplasia, EIN) and malignant (cancer, EMCA) endometria must be precisely distinguished for optimal management. EIN was objectively defined previously as a regression model incorporating manually traced histologic variables to predict clonal growth and cancer outcomes. Results from this early computational study were used to revise subjective endometrial precancer diagnostic criteria currently in use. We here use automated feature segmentation and updated machine learning algorithms to develop a new classification algorithm. Endometrial tissue from 148 patients was randomly separated into 72-patient training and 76-patient validation cohorts encompassing all 3 diagnostic classes. We applied image analysis software to keratin stained endometrial tissues to automatically segment whole-slide digital images into epithelium, cells, and nuclei and extract corresponding variables. A total of 1413 variables were culled to 75 based on random forest classification performance in a 3-group (NL, EIN, EMCA) model. This algorithm correctly classifies cases with 3-class error rates of 0.04 (training set) and 0.058 (validation set); and 2-class (NL vs. EIN+EMCA) error rate of 0.016 (training set) and 0 (validation set). The 4 most heavily weighted variables are surrogates of those previously identified in manual-segmentation machine learning studies (stromal and epithelial area percentages, and normalized epithelial surface lengths). Lesser weighted predictors include gland and lumen axis lengths and ratios, and individual cell measures. Automated image analysis and random forest classification algorithms can classify normal, premalignant, and malignant endometrial tissues. Highest predictive variables overlap with those discovered independently in early models based on manual segmentation.

Filamin A- and formin 2-dependent endocytosis regulates proliferation via the canonical Wnt pathway.

Actin-associated proteins regulate multiple cellular processes, including proliferation and differentiation, but the molecular mechanisms underlying these processes are unclear. Here, we report that the actin-binding protein filamin A (FlnA) physically interacts with the actin-nucleating protein formin 2 (Fmn2). Loss of FlnA and Fmn2 impairs proliferation, thereby generating multiple embryonic phenotypes, including microcephaly. FlnA interacts with the Wnt co-receptor Lrp6. Loss of FlnA and Fmn2 impairs Lrp6 endocytosis, downstream Gsk3ß activity, and ß-catenin accumulation in the nucleus. The proliferative defect in Flna and Fmn2 null neural progenitors is rescued by inhibiting Gsk3ß activity. Our findings thus reveal a novel mechanism whereby actin-associated proteins regulate proliferation by mediating the endocytosis and transportation of components in the canonical Wnt pathway. Moreover, the Fmn2-dependent signaling in this pathway parallels that seen in the non-canonical Wnt-dependent regulation of planar cell polarity through the Formin homology protein Daam. These studies provide evidence for integration of actin-associated processes in directing neuroepithelial proliferation.

A joint model for interval-censored functional decline trajectories under informative observation.

Multi-state models are useful for modelling disease progression where the state space of the process is used to represent the discrete disease status of subjects. Often, the disease process is only observed at clinical visits, and the schedule of these visits can depend on the disease status of patients. In such situations, the frequency and timing of observations may depend on transition times that are themselves unobserved in an interval-censored setting. There is a potential for bias if we model a disease process with informative observation times as a non-informative observation scheme with pre-specified examination times. In this paper, we develop a joint model for the disease and observation processes to ensure valid inference because the follow-up process may itself contain information about the disease process. The transitions for each subject are modelled using a Markov process, where bivariate subject-specific random effects are used to link the disease and observation models. Inference is based on a Bayesian framework, and we apply our joint model to the analysis of a large study examining functional decline trajectories of palliative care patients.

Toward a population-based approach to end-of-life care surveillance in Canada: initial efforts and lessons.

This paper describes a project undertaken by the Hospice Palliative End-of-Life Care Surveillance Team Network--one of four Cancer Surveillance and Epidemiology Networks established by the Canadian Partnership Against Cancer in 2009 to create information products that can be used to inform cancer control. The project was designed to improve the quality and use of existing electronic patient databases in its member organizations. The project's intent was to better understand terminally ill cancer patients in their final year of life, with noncancer as comparison. The network created an early design for a Web-based end-of-life care surveillance system prototype. Using a flagging process, anonymized data sets on cancer/ noncancer palliative patients and those who died in 2008-2009 were extracted and analyzed. The Australian palliative approach was adapted as the conceptual model based on the data sets available. Common data elements were defined then mapped to local data sets to create a common data set. Information products were created as online reports. Throughout the project, members were engaged in knowledge translation. Overall, the project was well received by network members. There are still major data-quality and linkage issues that require further work.

Conversion of Karnofsky Performance Status (KPS) and Eastern Cooperative Oncology Group Performance Status (ECOG) to Palliative Performance Scale (PPS), and the interchangeability of PPS and KPS in prognostic tools.

AIM: The aim of our study was to assess whether the Karnofsky Performance Status (KPS), the Eastern Cooperative Oncology Group (ECOG) Performance Status, and the Palliative Performance Scale (PPS) are interchangeable individually or within two prognostic tools: the Palliative Prognostic Score (PaP) and the Palliative Prognostic Index (PPI). METHODS: We performed a subset analysis of a prospective comparative study of functional and prognostic tools and clinician prediction of survival. We studied 955 patients with advanced life-limiting illnesses (cancer and noncancer) in the acute care and community settings. We used a descriptive statistical model and Spearman's rank correlation to assess these interchangeabilities. RESULTS: There is a direct positive linear relationship between the KPS and the PPS, and a direct negative linear relationship between these tools and the ECOG. Exchange of the KPS and the PPS was possible within the PaP and the PPI. CONCLUSION: The PPS and the KPS can be used interchangeably as functional tools and within prognostic tools. The ECOG is interchangeable with the PPS and the KPS, but this interchangeability is population-specific.

Inter-rater reliability of the bereavement risk assessment tool.

OBJECTIVE: The Bereavement Risk Assessment Tool (BRAT) was designed to consistently communicate information affecting bereavement outcomes; to predict the risk for difficult or complicated bereavement based on information obtained before the death; to consider resiliency as well as risk; and to assist in the efficacy and consistency of bereavement service allocation. Following initial development of the BRAT's 40 items and its clinical use, this study set out to test the BRAT for inter-rater reliability along with some basic validity measures. METHOD: Case studies were designed based on actual patients and families from a hospice palliative care program. Bereavement professionals were recruited via the internet. Thirty-six participants assessed BRAT items in 10 cases and then estimated one of 5 levels of risk for each case. These were compared with an expert group's assignment of risk. RESULTS: Inter-rater reliability for the 5-level risk scores yielded a Fleiss' kappa of 0.37 and an intra-class correlation (ICC) of 0.68 (95% CI 0.5-0.9). By collapsing scores into low and high risk groups, a kappa of 0.63 and an ICC of 0.66 (95% CI 0.5-0.9) was obtained. Participant-estimated risk scores yielded a kappa of 0.24. Although opinion varied on the tool's length, participants indicated it was well organized and easy to use with potential in assessment and allocation of bereavement services. Limitations of the study include a small sample size and the use of case studies. Limitations of the tool include the subjectivity of some items and ambiguousness of unchecked items. SIGNIFICANCE OF RESULTS: The collapsed BRAT risk levels show moderately good inter-rater reliability over clinical judgement alone. This study provides introductory evidence of a tool that can be used both prior to and following a death and, in conjunction with professional judgment, can assess the likelihood of bereavement complications.

Dietary views and habits of students in health professional vs. non-health professional graduate programs in a single university.

CONTEXT: Students enrolled in health professional (HP) programs receive varying amounts of credit hours dedicated to nutritional education, and obesity remains an issue in the United States among healthcare providers. OBJECTIVES: To assess whether HP students differ in nutrition and exercise habits from non-health professional (NHP) students at a single university, and whether any gender-related differences existed in those habits. METHODS: From September 25, 2018 to October 10, 2019, a 16-question multiple-choice survey was distributed via e-mail or in person to HP and NHP students enrolled at Nova Southeastern University (NSU) in Fort Lauderdale, Florida. Questions targeted participant dietary and exercise habits. Each question had five multiple-choice answer options, each of which was assigned a coded value to compare similarities and differences between the HP and NHP groups. RESULTS: Of 732 responses (569 HP, 163 NHP), results showed no statistically significant difference between enrollment groups (p>0.05) in any response parameter including consumption of sweets, fast food, red meat, caffeine, water, fruit, and vegetables. Comparisons among sexes demonstrated significant differences. Women consumed less red meat, water, and protein, and women participated in less exercise compared to men. Women also consumed more sweets compared to men. CONCLUSIONS: Results suggest that NSU students enrolled in HP and NHP programs have similar nutritional concepts and eating habits. This may indicate a need to strengthen nutritional education in dietary health and wellness for HP students.

Endometrial Tumor Classification by Histomorphology and Biomarkers in the Nurses' Health Study.

OBJECTIVE: Endometrial cancers have historically been classified by histomorphologic appearance, which is subject to interobserver disagreement. As molecular and biomarker testing has become increasingly available, the prognostic significance and accuracy of histomorphologic diagnoses have been questioned. To address these issues for a large, prospective cohort study, we provide the results of a centralized pathology review and biomarker analysis of all incidental endometrial carcinomas occurring between 1976 and 2012 in the Nurses' Health Study. METHODS: Routine histology of all (n = 360) cases was reviewed for histomorphologic diagnosis. Cases were subsequently planted in a tissue microarray to explore expression of a variety of biomarkers (e.g., ER, PR, p53, PTEN, PAX2, AMACR, HNF1ß, Napsin A, p16, PAX8, and GATA3). RESULTS: Histologic subtypes included endometrioid (87.2%), serous (5.6%), carcinosarcoma (3.9%), clear cell (1.7%), and mixed type (1.7%). Biomarker results within histologic subtypes were consistent with existing literature: abnormal p53 was frequent in serous cases (74%), and HNF1ß (67%), Napsin A (67%), and AMACR (83%) expression was frequent in clear cell carcinomas. Our dataset also allowed for examination of biomarker expression across non-preselected histologies. The results demonstrated that (1) HNF1ß was not specific for clear cell carcinoma, (2) TP53 mutations occurred across many histologies, and (3) GATA3 was expressed across multiple histotypes, with 75% of positive cases demonstrating high-grade features. CONCLUSIONS: Our findings establish the subtypes of endometrial cancer occurring in the Nurses' Health Study, corroborate the sensitivity of certain well-established biomarkers, and call into question previously identified associations between certain biomarkers (e.g., HNF1B) and particular histotypes.

Predicting survival in patients with advanced disease.

Prognostication is an important clinical skill for all clinicians, particularly those clinicians working with patients with advanced cancer. However, doctors can be hesitant about prognosticating without a fundamental understanding of how to formulate a prognosis more accurately and how to communicate the information with honesty and compassion. Irrespective of the underlying type of malignancy, most patients with advanced cancer experience a prolonged period of gradual decline (months/years) before a short phase of accelerated decline in the last month or two. The main indicators of this final phase are poor performance status, weight loss, symptoms such as anorexia, breathlessness or confusion and abnormalities on laboratory parameters (e.g. high white cell count, lymphopaenia, hyopalbuminaemia, elevated lactate dehydrogenase or C-reactive protein). The clinical estimate of survival remains a powerful independent prognostic indicator, often enhanced by experience, but research has only begun to understand the different biases affecting clinicians' estimates. More recent research has shown probabilistic predictions to be more accurate than temporal predictions. Simple, reliable and valid prognostic tools have been developed in recent years that can be used readily at the bedside of terminally ill cancer patients. The greatest accuracy occurs with the use of a combination of subjective prognostic judgements and objective validated tools. Communicating survival predictions is an important part of cancer care and guidelines exist for improving delivery of such information. Important cultural differences may influence communication strategies and should be recognised in clinical encounters. More well-designed studies of prognosis and its impact on decision making are needed. The benefits and limitations of prognostication should be considered in many clinical decisions.

A reliability and validity study of the Palliative Performance Scale.

BACKGROUND: The Palliative Performance Scale (PPS) was first introduced in1996 as a new tool for measurement of performance status in palliative care. PPS has been used in many countries and has been translated into other languages. METHODS: This study evaluated the reliability and validity of PPS. A web-based, case scenarios study with a test-retest format was used to determine reliability. Fifty-three participants were recruited and randomly divided into two groups, each evaluating 11 cases at two time points. The validity study was based on the content validation of 15 palliative care experts conducted over telephone interviews, with discussion on five themes: PPS as clinical assessment tool, the usefulness of PPS, PPS scores affecting decision making, the problems in using PPS, and the adequacy of PPS instruction. RESULTS: The intraclass correlation coefficients for absolute agreement were 0.959 and 0.964 for Group 1, at Time-1 and Time-2; 0.951 and 0.931 for Group 2, at Time-1 and Time-2 respectively. Results showed that the participants were consistent in their scoring over the two times, with a mean Cohen's kappa of 0.67 for Group 1 and 0.71 for Group 2. In the validity study, all experts agreed that PPS is a valuable clinical assessment tool in palliative care. Many of them have already incorporated PPS as part of their practice standard. CONCLUSION: The results of the reliability study demonstrated that PPS is a reliable tool. The validity study found that most experts did not feel a need to further modify PPS and, only two experts requested that some performance status measures be defined more clearly. Areas of PPS use include prognostication, disease monitoring, care planning, hospital resource allocation, clinical teaching and research. PPS is also a good communication tool between palliative care workers.

Correlation between Braden Scale and Palliative Performance Scale in advanced illness.

This study describes the significant correlation between the Braden Scale (BS) and the Palliative Performance Scale (PPS) in patients with advanced illness that has not been previously reported. The analysis was based on a prospective sequential case series of 664 patients suffering from advanced illness who were referred to a regional palliative medicine programme in Toronto, Canada. Baseline BS and PPS scores assessed within 24 hours of referral were considered for analysis. After controlling for age, gender, consult site and diagnosis (cancer versus non cancer), we observed a significant positive correlation between baseline PPS and BS scores (r = 0.885, P < 0.001). These findings suggest that for patients with advanced illness where BS is not routinely used, PPS could be considered as a proxy for pressure ulcer risk assessment.

Adiponectin, Leptin, and Insulin-Pathway Receptors as Endometrial Cancer Subtyping Markers.

Developing a system of molecular subtyping for endometrial tumors might improve insight into disease etiology and clinical prediction of patient outcomes. High body mass index (BMI) has been implicated in development of endometrial cancer through hormonal pathways and might influence tumor expression of biomarkers involved in BMI-sensitive pathways. We evaluated whether endometrial tumor expression of 7 markers from BMI-sensitive pathways of insulin resistance could effectively characterize molecular subtypes: adiponectin receptor 1, adiponectin receptor 2, leptin receptor, insulin receptor (beta subunit), insulin receptor substrate 1, insulin-like growth factor 1 receptor, and insulin-like growth factor 2 receptor. Using endometrial carcinoma tissue specimens from a case-only prospective sample of 360 women from the Nurses' Health Study, we scored categorical immunohistochemical measurements of protein expression for each marker. Logistic regression was used to estimate associations between endometrial cancer risk factors, especially BMI, and tumor marker expression. Proportional hazard modeling was performed to estimate associations between marker expression and time to all-cause mortality as well as time to endometrial cancer-specific mortality. No association was observed between BMI and tumor expression of any marker. No marker was associated with time to either all-cause mortality or endometrial cancer-specific mortality in models with or without standard clinical predictors of patient mortality (tumor stage, grade, and histologic type). It did not appear that any of the markers evaluated here could be used effectively to define molecular subtypes of endometrial cancer.

Meta-analysis of survival prediction with Palliative Performance Scale.

This paper aims to reconcile the use of Palliative Performance Scale (PPSv2) for survival prediction in palliative care through an international collaborative study by five research groups. The study involves an individual patient data meta-analysis on 1,808 patients from four original datasets to reanalyze their survival patterns by age, gender, cancer status, and initial PPS score. Our findings reveal a strong association between PPS and survival across the four datasets. The Kaplan-Meier survival curves show each PPS level as distinct, with a strong ordering effect in which higher PPS levels are associated with increased length of survival. Using a stratified Cox proportional hazard model to adjust for study differences, we found females lived significantly longer than males, with a further decrease in hazard for females not diagnosed with cancer. Further work is needed to refine the reporting of survival times/probabilities and to improve prediction accuracy with the inclusion of other variables in the models.

The Spanish Adaptation of the Palliative Performance Scale (Version 2) Among Cancer Patients at the End of Life: Psychometric Properties.

BACKGROUND: Palliative Performance Scale (PPS) is a reliable tool to assess performance status in cancer patients receiving palliative care (PC). Spanish validated and culturally adapted tools are needed. OBJECTIVES: The objectives are to develop PPS translation and cross-cultural adaptation into Spanish and to assess its psychometric properties. DESIGN: Translation process with cross-cultural adaptation to produce Spanish Palliative Performance Scale (PPS-SPANISH). SETTINGS: PC Team at one University hospital in Spain. PARTICIPANTS: Fifteen advanced cancer patients (60 assessments) were included for PPS translation and validation and 250 patients for cross-sectional analysis. All participants were recruited at oncology ward, emergency area, and outpatient clinic by PC team professionals. Informed consent was given. Average age was 66.4 ± 13 years (60% men). METHODS: The process is designed in three steps. In Step 1, PPS translation and reverse translation into Spanish (three bilingual speakers) and linguistic complexity measurement were performed. In Step 2, readability and intelligibility assessment was carried out. In Step 3, a pilot study was conducted to assess test-retest reliability followed by a cross-sectional study to measure internal consistency. Inclusion criteria were the same for two samples. Demographic data were also analyzed by descriptive statistics. RESULTS: Following cultural, linguistic, and grammatical adaptation, PPS-SPANISH was readable and reliable. The analysis of the test-retest reliability after 48 hours showed intraclass correlations >0.60. Cronbach's alpha coefficient was 0.99 (0.988-0.992). There was high agreement with other functional assessment tools (Barthel Index and Karnofsky Performance Status Index). CONCLUSIONS: PPS-SPANISH showed reliability and validity, and it is suitable to assess performance status in cancer patients receiving PC.

Endometrial Cancer Risk Factors, Hormone Receptors, and Mortality Prediction.

Background: Endometrial tumors arise from a hormonally responsive tissue. Defining subtypes by hormone receptor expression might better inform etiology and prediction of patient outcomes. We evaluated the potential role of tumor estrogen receptor (ER) and progesterone receptor (PR) expression to define endometrial cancer subtypes.Methods: We measured semi-continuous ER and PR protein expression in tissue specimens from 360 endometrial primary tumors from the Nurses' Health Study. To explore the impact of different definitions of marker positivity, we dichotomized ER and PR expression at different cut points in increments of 5% positive cells. Logistic regression was used to estimate associations between endometrial cancer risk factors, such as body mass index, with dichotomous ER or PR status. Reclassification statistics were used to assess whether adding dichotomous ER or PR status to standard prognostic factors of stage, grade, and histologic type would improve endometrial cancer-specific mortality prediction.Results: Compared with not being obese, obesity increased the odds of having an ER-positive tumor at cut points of 0% to 20% [maximum OR, 2.92; 95% confidence interval (CI), 1.34-6.33] as well as the odds of having a PR-positive tumor at cut points of 70% to 90% (maximum OR, 2.53; 95% CI, 1.36-4.68). Adding dichotomous tumor ER or PR status to the panel of standard predictors did not improve both model discrimination and calibration.Conclusions: Obesity may be associated with greater endometrial tumor expression of ER and PR. Adding either marker does not appear to improve mortality prediction beyond the standard predictors.Impact: Body mass index might explain some of the biological variation among endometrial tumors. Cancer Epidemiol Biomarkers Prev; 26(5); 727-35. ©2017 AACR.

Factors associated with health-related quality of life among outpatients with major depressive disorder: a STAR*D report.

OBJECTIVE: Major depressive disorder (MDD) is often chronic and is often associated with significant morbidity and mortality. The importance of assessing disability and health-related quality of life (HRQOL) in patients with MDD has only recently been recognized. The aim of this study was to examine sociodemographic and clinical correlates of HRQOL in a large cohort of outpatients with MDD. METHOD: Baseline assessments were completed for 1500 consecutive patients enrolled in the Sequenced Treatment Alternatives to Relieve Depression trial, including sociodemographic characteristics and measures of depressive symptom severity, clinical features, and HRQOL. Multiple domains of HRQOL were assessed with the 12-item Short Form Health Survey, the Work and Social Adjustment Scale, and the Quality of Life Enjoyment and Satisfaction Questionnaire. The current analyses were conducted on HRQOL data available for 1397 of the 1500 subjects. RESULTS: Greater symptom severity was associated with reduced HRQOL by all measures. Even after age and symptom severity were controlled for, a number of clinical features and sociodemographic characteristics were independently associated with HRQOL in multiple domains, including age at onset of MDD, ethnicity, marital status, employment status, education level, insurance status, and monthly household income. CONCLUSION: Results strongly suggest the need to assess HRQOL in addition to symptoms in order to gauge the true severity of MDD. This study also highlights the necessity of measuring HRQOL in multiple domains. These results have implications for the assessment of remission and functional recovery in the treatment of MDD.

Anesthetic considerations for magnetic seizure therapy: a novel therapy for severe depression.

Electroconvulsive therapy (ECT) is a highly effective treatment for severe depression. However, its use is associated with significant posttreatment cognitive impairment. Magnetic seizure therapy (MST) was developed as an alternative therapy that could reduce postseizure side effects through the induction of more "focal" seizure activity. Using an open-parallel study design, we compared 20 case-matched patients undergoing a series of either ECT or MST procedures with respect to their anesthetic, muscle relaxant, and cardiovascular drug requirements, effects on cardiovascular and electroencephalographic bispectral index (BIS) values, and early recovery times. We found that MST was associated with a reduced time to orientation (4 +/- 1 versus 18 +/- 5 min; P < 0.01) compared with ECT. To minimize residual muscle paralysis after MST, a reduction in the succinylcholine dosage (38 +/- 17 versus 97 +/- 2 mg; P < 0.01) was required. The BIS values were higher before, and lower immediately after, the stimulus was applied in the MST (versus ECT) group. The Hamilton depression rating scale score was significantly reduced from the baseline value in both treatment groups; however, the posttreatment score was lower after the series of ECT treatments (6 +/- 6 versus 14 +/- 10; P < 0.05). We conclude that MST was associated with a decreased requirement for muscle relaxants, reduced variability in the BIS values after seizure induction, and a more rapid recovery of cognitive function compared with ECT. Further studies are required to evaluate the antidepressant efficacy of MST versus ECT when they are administered at comparable levels of cerebral stimulation.