Inpatient Hospital Costs and Route of Hysterectomy for Management of Benign Uterine Disease in the 90-Day Global Billing Period.

OBJECTIVE: To compare inpatient hospital costs and complication rates within the 90-day global billing period among routes of hysterectomy. METHODS: The Premier Healthcare Database was used to identify patients who underwent hysterectomy between 2000 and 2020. Current Procedural Terminology codes were used to group patients based on route of hysterectomy. Comorbidities and complications were identified using International Classification of Diseases codes. Fixed, variable, and total costs for inpatient care were compared. Fixed costs consist of costs that are set for the case, such as operating room time or surgeon costs. Variable costs include disposable and reusable items that are billed additionally. Total costs equal fixed and variable costs combined. Data were analyzed using analysis of variance, t test, and χ2 test, as appropriate. Factors independently associated with increased total costs were assessed using linear mixed effects models. Multivariate logistic regression was performed to evaluate associations between the route of surgery and complication rates. RESULTS: A cohort of 400,977 patients were identified and grouped by route of hysterectomy. Vaginal hysterectomy demonstrated the lowest inpatient total cost ($6,524.00 [interquartile range $4,831.60, $8,785.70]), and robotic-assisted laparoscopic hysterectomy had the highest total cost ($9,386.80 [interquartile range $6,912.40, $12,506.90]). These differences persisted with fixed and variable costs. High-volume laparoscopic and robotic surgeons (more than 50 cases per year) had a decrease in the cost difference when compared with costs of vaginal hysterectomy. Abdominal hysterectomy had a higher rate of complications relative to vaginal hysterectomy (adjusted odds ratio [aOR] 1.52, 95% CI, 1.39-1.67), whereas laparoscopic (aOR 0.85, 95% CI, 0.80-0.89) and robotic-assisted (aOR 0.92, 95% CI, 0.84-1.00) hysterectomy had lower rates of complications compared with vaginal hysterectomy. CONCLUSION: Robotic-assisted hysterectomy is associated with higher surgical costs compared with other approaches, even when accounting for surgeon volume. Complication rates are low for minimally invasive surgery, and it is unlikely that the robotic-assisted approach provides an appreciable improvement in perioperative outcomes.

A Trauma-Informed and Gender-Inclusive Medical Nomenclature.

Transgender individuals face discrimination in several contexts and spaces, which exacerbates dysphoria and disparities in mental and physical well-being. Gender-exclusionary environments in the health care system lead to limitations in access to care and unaddressed health care needs. The full spectrum of gender is often not recognized in the field of medicine, which is predicated on the binary of male and female. Obstetrics and gynecology is societally viewed as a field for cisgender women, but transgender individuals can, and do, benefit from services offered by obstetricians and gynecologists. It is imperative that all specialties consider which aspects of care can be altered to promote the safety and health care of medically marginalized groups, including transgender patients. Alternative vocabulary to gendered language commonly used in medicine is discussed in three contexts: patient counseling, medical records, and institutional language. Understanding and using gender-inclusive language is an important step to create safer, respectful, affirming spaces for transgender people to receive medical care.

EMT Subtype Influences Epithelial Plasticity and Mode of Cell Migration.

Epithelial-mesenchymal transition (EMT) is strongly implicated in tumor cell invasion and metastasis. EMT is thought to be regulated primarily at the transcriptional level through the repressive activity of EMT transcription factors. However, these classical mechanisms have been parsed out almost exclusively in vitro, leaving questions about the programs driving EMT in physiological contexts. Here, using a lineage-labeled mouse model of pancreatic ductal adenocarcinoma to study EMT in vivo, we found that most tumors lose their epithelial phenotype through an alternative program involving protein internalization rather than transcriptional repression, resulting in a "partial EMT" phenotype. Carcinoma cells utilizing this program migrate as clusters, contrasting with the single-cell migration pattern associated with traditionally defined EMT mechanisms. Moreover, many breast and colorectal cancer cell lines utilize this alternative program to undergo EMT. Collectively, these results suggest that carcinoma cells have different ways of losing their epithelial program, resulting in distinct modes of invasion and dissemination.

Combining Machine Learning and Nanofluidic Technology To Diagnose Pancreatic Cancer Using Exosomes.

Circulating exosomes contain a wealth of proteomic and genetic information, presenting an enormous opportunity in cancer diagnostics. While microfluidic approaches have been used to successfully isolate cells from complex samples, scaling these approaches for exosome isolation has been limited by the low throughput and susceptibility to clogging of nanofluidics. Moreover, the analysis of exosomal biomarkers is confounded by substantial heterogeneity between patients and within a tumor itself. To address these challenges, we developed a multichannel nanofluidic system to analyze crude clinical samples. Using this platform, we isolated exosomes from healthy and diseased murine and clinical cohorts, profiled the RNA cargo inside of these exosomes, and applied a machine learning algorithm to generate predictive panels that could identify samples derived from heterogeneous cancer-bearing individuals. Using this approach, we classified cancer and precancer mice from healthy controls, as well as pancreatic cancer patients from healthy controls, in blinded studies.

Metastatic progression is associated with dynamic changes in the local microenvironment.

Most cancer-associated deaths result from metastasis. However, it remains unknown whether the size, microenvironment or other features of a metastatic lesion dictate its behaviour or determine the efficacy of chemotherapy in the adjuvant (micrometastatic) setting. Here we delineate the natural history of metastasis in an autochthonous model of pancreatic ductal adenocarcinoma (PDAC), using lineage tracing to examine the evolution of disseminated cancer cells and their associated microenvironment. With increasing size, lesions shift from mesenchymal to epithelial histology, become hypovascular and accumulate a desmoplastic stroma, ultimately recapitulating the primary tumours from which they arose. Moreover, treatment with gemcitabine and nab-paclitaxel significantly reduces the overall number of metastases by inducing cell death in lesions of all sizes, challenging the paradigm that PDAC stroma imposes a critical barrier to drug delivery. These results illuminate the cellular dynamics of metastatic progression and suggest that adjuvant chemotherapy affords a survival benefit by directly targeting micrometastases.