Real-world patient- and caregiver-reported outcomes in advanced breast cancer

Background

Advanced breast cancer (abc) represents a substantial burden for patients and caregivers. In the present study, we aimed to estimate quality of life (qol), utility, productivity loss, pain, health care resource utilization, and costs for patients with abc, and qol, utility, and productivity loss for their caregivers.

Methods

This multicentre prospective non-interventional study was conducted in Canada. Eligible participants were postmenopausal women with estrogen receptor-positive, her2-negative unresectable abc and their caregivers. Validated questionnaires were used to measure qol, utility, productivity loss, and pain. Patients and caregivers were classified into 4 health states typically used in oncology economic modelling: first-line progression-free (1l-pf), first-line progressive disease (1l-pd), second- or subsequent-line progression-free (≥2l-pf), and second- or subsequent-line progressive disease (≥2l-pd).

Results

Most patients and caregivers accepted to participate, with total recruitment of 202 patients and 78 caregivers. Compared with patients in pf, patients in pd had lower mean qol scores (52.9 ± 29.9 for 1l-pd vs. 68.2 ± 23.2 for 1l-pf, and 54.0 ± 23.6 for ≥2l-pd vs. 66.0 ± 22.1 for ≥2l-pf), lower mean utility values (0.64 ± 0.22 for 1l-pd vs. 0.73 ± 0.20 for 1l-pf, and 0.65 ± 0.25 for ≥2l-pd vs. 0.74 ± 0.18 for ≥2l-pf), and greater productivity loss (39.4 ± 27.7 for 1l-pd vs. 27.5 ± 30.1 for 1l-pf, and 37.6 ± 29.2 for ≥2l-pd vs. 32.0 ± 29.0 for ≥2l-pf). Compared with caregivers of patients in pf, caregivers of patients in pd had lower qol scores and utility values, and greater productivity loss.

Conclusions

Study results indicate that, for patients and caregivers, pd health states are associated with a deterioration of qol and utility and a decrease in productivity in both 1l and ≥2l.

Quantum Chiral Higher Spin Gravity

An example of a higher spin gravity in four-dimensional flat space has recently been constructed by D. Ponomarev and E. D. Skvortsov, J. Phys. A, 50, 095401(2017). This theory is chiral and the action is written in the light-cone gauge. The theory has certain stringy features, e.g., admits Chan-Paton factors. We show that the theory is consistent, both at the classical and quantum level. Even though the interactions are nontrivial, due to the coupling conspiracy all tree level amplitudes vanish on shell. The loop corrections also vanish. Therefore, the full quantum S matrix is one and the theory is consistent with the numerous no-go theorems. This provides the first example of a (quantum) interacting higher spin gravity with an action. We argue that higher spin gravities in anti-de Sitter space should display the same features.

Therapeutic cancer vaccine: building the future from lessons of the past

Anti-cancer vaccines have raised many hopes from the start of immunotherapy but have not yet been clinically successful. The few positive results of anti-cancer vaccines have been observed in clinical situations of low tumor burden or preneoplastic lesions. Several new concepts and new results reposition this therapeutic approach in the field of immunotherapy. Indeed, cancers that respond to anti-PD-1/PD-L1 (20-30%) are those that are infiltrated by anti-tumor T cells with an inflammatory infiltrate. However, 70% of cancers do not appear to have an anti-tumor immune reaction in the tumor microenvironment. To induce this anti-tumor immunity, therapeutic combinations between vaccines and anti-PD-1/PD-L1 are being evaluated. In addition, the identification of neoepitopes against which the immune system is less tolerated is giving rise to a new enthusiasm by the first clinical results of the vaccine including these neoepitopes in humans. The ability of anti-cancer vaccines to induce a population of anti-tumor T cells called memory resident T cells that play an important role in immunosurveillance is also a new criterion to consider in the design of therapeutic vaccines.

Cytogenetic Findings on 11,451 Cases of Amniocentesis in Hanoi, Vietnam

Since the 1960s, amniocentesis has become a routine procedure performed in prenatal diagnostic clinics. This study aims to depict the results of amniocentesis, the frequency of chromosomal abnormality and emphasize on amniocentesis indications. A retrospective study was conducted on 11,451 cases who were referred to the Prenatal Diagnosis Center, the National Hospital of Obstetrics and Gynecology, Hanoi, Vietnam from 2012 to 2016. The rate of chromosomal abnormality was 6.7%. The chromosomal aberration in the group with mother or father carrying balanced parental translocations accounted for the highest rate of 22.0%. Triploidy was 1.2%, autosomal chromosome aberration was 59.7%, sex chromosome was 8.3%, and structural rearrangements was 30.8%. Trisomy 21 was the most frequent disorder founded in abnormal ultrasound findings (47.4%), following by the advanced maternal age (44.1%). The large sample size of this study provided reliable evidence to support the development of prenatal counseling and pregnancy management programs.

Sleeve Gastrectomy and Left Ventricular Assist Device for Heart Transplant

BACKGROUND AND OBJECTIVES

Heart failure (HF) is a severe obesity-related comorbidity. Many patients with end-stage HF eventually require cardiac transplantation for long-term survival. These patients may be precluded from enrollment in heart transplant programs secondary to morbid obesity. We propose a pathway involving sleeve gastrectomy (SG) for patients with morbid obesity and HF to afford cardiac transplantation eligibility.

METHODS

Three patients with HF and morbid obesity underwent implantation of a left ventricular assist device (LVAD) and SG at an academic tertiary care institution in Washington, DC. This retrospective review from April 2012 through January 2017 examines the perioperative course of these 3 patients with regard to bariatric and cardiac indices, including ejection fraction (EF), HF classification, comorbid diseases, and percentages of total weight loss (%TWL) and excess weight loss (%EWL).

RESULTS

All three patients underwent LVAD placement as a bridge to transplant but were excluded from cardiac transplantation secondary to body mass index (BMI) and were referred for bariatric surgery. All have demonstrated considerable weight loss, with average decrease in BMI of 19 points, 39% TWL, and 81% EWL at a mean of 44 months after SG. Two patients have gone on to receive heart transplants, with near normalization of their EF.

CONCLUSION

LVAD and SG constitute a feasible pathway to cardiac transplantation in morbidly obese patients with end-stage HF. LVAD permits temporary cardiac support, whereas SG assists in efficacious weight loss. We explore SG as a durable weight loss option in patients with HF, with LVAD to improve eligibility for orthotopic cardiac transplantation.

Identification of a small molecule inhibitor of the aminoglycoside 6'-N-acetyltransferase type Ib [AAC(6')-Ib] using mixture-based combinatorial libraries

The aminoglycoside, 6'-N-acetyltransferase type Ib [AAC(6')-Ib] is the most widely distributed enzyme among AAC(6')-I-producing Gram-negative pathogens and confers resistance to clinically relevant aminoglycosides, including amikacin. This enzyme is therefore an ideal target for enzymatic inhibitors that could overcome resistance to aminoglycosides. The search for inhibitors was carried out using mixture-based combinatorial libraries, the scaffold ranking approach, and the positional scanning strategy. A library with high inhibitory activity had pyrrolidine pentamine scaffold and was selected for further analysis. This library contained 738,192 compounds with functionalities derived from 26 different amino acids (R1, R2 and R3) and 42 different carboxylic acids (R4) in four R-group functionalities. The most active compounds all contained S-phenyl (R1 and R3) and S-hydromethyl (R2) functionalities at three locations and differed at the R4 position. The compound containing 3-phenylbutyl at R4 (compound 206) was a robust enzymatic inhibitor in vitro, in combination with amikacin it potentiated the inhibition of growth of three resistant bacteria in culture, and it improved survival when used as treatment of Galleria mellonella infected with aac(6')-Ib-harboring Klebsiella pneumoniae and Acinetobacter baumannii strains.

How do caregivers understand and respond to unsettled infant behaviour in Vietnam? A qualitative study

BACKGROUND

Unsettled infant behaviours are a common source of concern for new parents and have been associated with perinatal common mental disorders amongst women in high-income settings. There is little evidence about how unsettled infant behaviours are understood and managed in low and lower-middle income countries. This study aimed to describe caregivers' understandings of, and responses to, unsettled infant behaviours in Vietnam and their family caregiving contexts.

METHODS

Women who were mothers of infants aged 0-6 months were purposively recruited from two sites in Thua Thien Hue Province, Vietnam (one urban and one rural). An additional group of women who were grandmothers were recruited by snowball sampling. Data were collected in semi-structured interviews about demographic information, infant feeding practices, descriptions of infant crying episodes, beliefs about why infants cry, settling strategies, infant sleeping arrangements and sources of advice on infant care. Translated interview transcripts were analysed thematically.

RESULTS

Twenty-four interviews were undertaken (21 with mothers and 3 with grandmothers). Five major themes emerged from the data after analysis: infant settling techniques, sources of information on unsettled infant behaviour, understandings of the causes of infant crying, the emotional responses of caregivers and the intergenerational household context. Infants were commonly cared for by people from multiple generations, particularly during the day. Infant settling was characterized by attending to infants immediately, breastfeeding and bed-sharing with parents during the night. Most mothers received advice on caregiving from family members. Infant crying was attributed to hunger and loneliness, as well as traditional beliefs that the infant was being upset by 'ghosts' or becoming 'hot'. Women described feeling anxious, frustrated and helpless in relation to unsettled behaviours amongst their infants.

CONCLUSIONS

Educational interventions on interpreting infant cues, infant sleep requirements and bed sharing may be appropriate in Vietnam if multiple generations are included and traditional beliefs about infant crying are addressed.

An end-to-end deep learning architecture for extracting protein-protein interactions affected by genetic mutations

The BioCreative VI Track IV (mining protein interactions and mutations for precision medicine) challenge was organized in 2017 with the goal of applying biomedical text mining methods to support advancements in precision medicine approaches. As part of the challenge, a new dataset was introduced for the purpose of building a supervised relation extraction model capable of taking a test article and returning a list of interacting protein pairs identified by their Entrez Gene IDs. Specifically, such pairs represent proteins participating in a binary protein–protein interaction relation where the interaction is additionally affected by a genetic mutation—referred to as a PPIm relation. In this study, we explore an end-to-end approach for PPIm relation extraction by deploying a three-component pipeline involving deep learning-based named-entity recognition and relation classification models along with a knowledge-based approach for gene normalization. We propose several recall-focused improvements to our original challenge entry that placed second when matching on Entrez Gene ID (exact matching) and on HomoloGene ID. On exact matching, the improved system achieved new competitive test results of 37.78% micro-F1 with a precision of 38.22% and recall of 37.34% that corresponds to an improvement from the prior best system by approximately three micro-F1 points. When matching on HomoloGene IDs, we report similarly competitive test results at 46.17% micro-F1 with a precision and recall of 46.67 and 45.59%, respectively, corresponding to an improvement of more than eight micro-F1 points over the prior best result. The code for our deep learning system is made publicly available at https://github.com/bionlproc/biocppi_extraction.

Predicting mental conditions based on "history of present illness" in psychiatric notes with deep neural networks

BACKGROUND

Applications of natural language processing to mental health notes are not common given the sensitive nature of the associated narratives. The CEGS N-GRID 2016 Shared Task in Clinical Natural Language Processing (NLP) changed this scenario by providing the first set of neuropsychiatric notes to participants. This study summarizes our efforts and results in proposing a novel data use case for this dataset as part of the third track in this shared task.

OBJECTIVE

We explore the feasibility and effectiveness of predicting a set of common mental conditions a patient has based on the short textual description of patient's history of present illness typically occurring in the beginning of a psychiatric initial evaluation note.

MATERIALS AND METHODS

We clean and process the 1000 records made available through the N-GRID clinical NLP task into a key-value dictionary and build a dataset of 986 examples for which there is a narrative for history of present illness as well as Yes/No responses with regards to presence of specific mental conditions. We propose two independent deep neural network models: one based on convolutional neural networks (CNN) and another based on recurrent neural networks with hierarchical attention (ReHAN), the latter of which allows for interpretation of model decisions. We conduct experiments to compare these methods to each other and to baselines based on linear models and named entity recognition (NER).

RESULTS

Our CNN model with optimized thresholding of output probability estimates achieves best overall mean micro-F score of 63.144% for 11 common mental conditions with statistically significant gains (p<0.05) over all other models. The ReHAN model with interpretable attention mechanism scored 61.904% mean micro-F1 score. Both models' improvements over baseline models (support vector machines and NER) are statistically significant. The ReHAN model additionally aids in interpretation of the results by surfacing important words and sentences that lead to a particular prediction for each instance.

CONCLUSIONS

Although the history of present illness is a short text segment averaging 300 words, it is a good predictor for a few conditions such as anxiety, depression, panic disorder, and attention deficit hyperactivity disorder. Proposed CNN and RNN models outperform baseline approaches and complement each other when evaluating on a per-label basis.

Tissue-resident memory T cells play a key role in the efficacy of cancer vaccines

Resident memory CD8⁺T cells (T_RM) usually defined by the CD103 marker represent a new subset of long-lived memory T cells that remain in the tissues. We directly demonstrate their specific role in cancer vaccine-induced tumor regression. In human, they also seem to play a major role in tumor immunosurveillance.

Extracting Drug-Drug Interactions with Word and Character-Level Recurrent Neural Networks

Drug-drug interactions (DDIs) are known to be responsible for nearly a third of all adverse drug reactions. Hence several current efforts focus on extracting signal from EMRs to prioritize DDIs that need further exploration. To this end, being able to extract explicit mentions of DDIs in free text narratives is an important task. In this paper, we explore recurrent neural network (RNN) architectures to detect and classify DDIs from unstructured text using the DDIExtraction dataset from the SemEval 2013 (task 9) shared task. Our methods are in line with those used in other recent deep learning efforts for relation extraction including DDI extraction. However, to our knowledge, we are the first to investigate the potential of character-level RNNs (Char-RNNs) for DDI extraction (and relation extraction in general). Furthermore, we explore a simple but effective model bootstrapping method to (a). build model averaging ensembles, (b). derive confidence intervals around mean micro-F scores (MMF), and (c). assess the average behavior of our methods. Without any rule based filtering of negative examples, a popular heuristic used by most earlier efforts, we achieve an MMF of 69.13. By adding simple replicable heuristics to filter negative instances we are able to achieve an MMF of 70.38. Furthermore, our best ensembles produce micro F-scores of 70.81 (without filtering) and 72.13 (with filtering), which are superior to metrics reported in published results. Although Char-RNNs turnout to be inferior to regular word based RNN models in overall comparisons, we find that ensembling models from both architectures results in nontrivial gains over simply using either alone, indicating that they complement each other.

Sensory profile and volatile aroma composition of reduced alcohol Merlot wines fermented with Metschnikowia pulcherrima and Saccharomyces uvarum

Strategies for production of wines containing lower alcohol concentrations are in strong demand, for reasons of quality, health, and taxation. Development and application of wine yeasts that are less efficient at transforming grape sugars into ethanol has the potential to allow winemakers the freedom to make lower alcohol wines from grapes harvested at optimal ripeness, without the need for post-fermentation processes aimed at removing ethanol. We have recently shown that two non-conventional wine yeast species Metschnikowia pulcherrima and Saccharomyces uvarum were both able to produce wine with reduced alcohol concentration. Both species produced laboratory-scale wines with markedly different volatile aroma compound composition relative to Saccharomyces cerevisiae. This work describes the volatile composition and sensory profiles of reduced-alcohol pilot-scale Merlot wines produced with M. pulcherrima and S. uvarum. Wines fermented with M. pulcherrima contained 1.0% v/v less ethanol than S. cerevisiae fermented wines, while those fermented with S. uvarum showed a 1.7% v/v reduction in ethanol. Compared to S. cerevisiae ferments, wines produced with M. pulcherrima showed higher concentrations of ethyl acetate, total esters, total higher alcohols and total sulfur compounds, while wines fermented with S. uvarum were characterised by the highest total concentration of higher alcohols. Sensorially, M. pulcherrima wines received relatively high scores for sensory descriptors such as red fruit and fruit flavour and overall exhibited a sensory profile similar to that of wine made with S. cerevisiae, whereas the main sensory descriptors associated with wines fermented with S. uvarum were barnyard and meat. This work demonstrates the successful application of M. pulcherrima AWRI3050 for the production of pilot-scale red wines with reduced alcohol concentration and highlights the need for rigorous evaluation of non-conventional yeasts with regard to their sensory impacts.

A Rare Case of Tropical Pyomysitis Acquired on Vacation in a Healthy Male

INTRODUCTION

Pyomyositis has traditionally been considered a tropical disease. Increasing prevalence has been observed in more northern climates, especially with HIV, immunosuppression, and IV drug abuse as predisposing factors. Pyomyositis has the tendency to mimic other conditions, such as muscle contusion, necrotizing fasciitis, or septic arthritis. The rarity of this disease and non-specificity of its symptoms often lead to delay in appropriate diagnosis and treatment.

CASE

24-year-old man, seen 2 days prior in orthopedics clinic and the Emergency Department for persistent gluteal pain thought to be due to right-sided sciatica, was admitted following worsening pain, diffuse generalized weakness with polyarthralgias and myalgias These symptoms were associated with night sweats, shaking chills, and difficulty walking. Prior to onset of symptoms, the patient vacationed in Cayman Islands and experienced a stingray bite on his right hand as well as numerous cuts on rocks in stagnant waters. He was febrile with WBC count of 18.7 K/ μL and was found to have methicillin-sensitive Staphylococcus aureus (MSSA); bacteremia. Magnetic resonance imaging (MRI); of his lumbar spine on admission was unremarkable. Repeat MRI 4 days later showed extensive inflammation within musculature with multiple abscesses around right sciatic foramen and septic arthritis of the sacroiliac joint. The patient was subsequently diagnosed with MSSA septic polyarthritis and required several orthopedic procedures. Infectious and oncologic work up was unremarkable. Transesophageal echocardiogram showed 0.3 cm x 0.5 cm aortic valve vegetation, which was managed medically. Repeat MRI 11 days after initiation of appropriate antibiotics and surgeries showed improvement in muscular edema. Based on the MSSA susceptibilities, the patient was treated with 6 weeks of intravenous cefazolin and 2 weeks of oral cephalexin thereafter.

DISCUSSION

Awareness of tropical pyomyositis in colder climates remains scarce, although cases have been reported in immunosuppressed patients. However, in healthy patients, accurate history of travel and trauma is important in evaluation for predisposing factors for pyomyositis. Early antibiotic and appropriate surgical interventions are imperative for management of this disease in order to prevent systemic toxicity, dissemination of infection, and long-term debility.