"The Equipoise Ruler:" A National Survey on Surgeon Judgment about the Value of Surgery.

OBJECTIVE: The objective of this study was to understand professional norms regarding the value of surgery. SUMMARY BACKGROUND DATA: Agreed-upon professional norms may improve surgical decision making by contextualizing the nature of surgical treatment for patients. However, the extent to which these norms exist among surgeons practicing in the US is not known. METHODS: We administered a survey with 30 exemplar cases asking surgeons to use their best judgement to place each case on a scale ranging from "Definitely would do this surgery" to "Definitely would not do this surgery." We then asked surgeons to repeat their assessments after providing responses from the first survey. We interviewed respondents to characterize their rationale. RESULTS: We received 580 responses, a response rate of 28.5%. For 19 of 30 cases there was consensus (≥60% agreement) about the value of surgery (range 63% - 99%). There was little within-case variation when the mode was for surgery and more variation when the mode was against surgery or equipoise. Exposure to peer response increased the number of cases with consensus. Women were more likely to endorse a non-operative approach when treatment had high mortality. Specialists were less likely to operate for salvage procedures. Surgeons noted their clinical practice was to withhold judgment and let patients decide despite their assessment. CONCLUSIONS: Professional judgment about the value of surgery exists along a continuum. While there is less variation in judgment for cases that are highly beneficial, consensus can be improved by exposure to the assessments of peers.

A Four-Arm Randomized Clinical Trial of Topical Pain Control for Sentinel Node Radiotracer Injections in Patients with Breast Cancer.

BACKGROUND: Radioactive tracer injections for breast cancer sentinel lymph node mapping can be painful. In this randomized trial, we compared four approaches to topical pain control for radiotracer injections. METHODS: Breast cancer patients were randomized (9 April 2021-8 May 2022) to receive the institutional standard of ice prior to injection (n = 44), or one of three treatments: ice plus a vibrating distraction device (Buzzy®; n = 39), 4% lidocaine patch (n = 44), or 4% lidocaine patch plus ice plus Buzzy® (n = 40). Patients completed the Wong-Baker FACES® pain score (primary outcome) and a satisfaction with pain control received scale (secondary). Nuclear medicine technologists (n = 8) rated perceived pain control and ease of administration for each patient. At study conclusion, technologists rank-ordered treatments. Data were analyzed as intention-to-treat. Wilcoxon rank-sum tests were used to compare pain scores of control versus pooled treatment arms (primary) and then control to each treatment arm individually (secondary). RESULTS: There were no differences in pain scores between the control and treatment groups, both pooled and individually. Eighty-five percent of patients were 'satisfied/very satisfied' with treatment received, with no differences between groups. No differences in providers' perceptions of pain were observed, although providers perceived treatments involving Buzzy© more difficult to administer (p < 0.001). Providers rated lidocaine patch as the easiest, with ice being second. CONCLUSION: In this randomized trial, no differences in patient-reported pain or satisfaction with treatment was observed between ice and other topical treatments. Providers found treatments using Buzzy® more difficult to administer. Given patient satisfaction and ease of administration, ice is a reasonable standard.

Validation of the AJCC 8th Edition Breast Cancer Prognostic Staging System in Legacy Alliance Trials (AFT-01).

BACKGROUND: The 8th edition American Joint Committee on Cancer staging system combined anatomic stage (AS) with receptor status and grade to create prognostic stage (PS). PS has been validated in single-institution and cancer registry studies; however, missing human epidermal growth factor receptor 2 (HER2) status and variable treatment and follow-up create limitations. OBJECTIVE: Our objective was to compare the relative prognostic ability of PS versus AS to predict survival using breast cancer clinical trial data. METHODS: Women with non-metastatic breast cancer enrolled in six Alliance for Clinical Trials in Oncology trials were included (enrollment years 1997-2010). AS and PS were constructed using pathological tumor size, nodal status, estrogen receptor (ER), progesterone receptor (PR), HER2 status, and grade. Unadjusted Cox proportional hazard models were estimated to predict overall survival within 5 years, with AS and PS as predictor variables. The relative predictive power of staging models was assessed by comparing Harrell concordance indices (C-indices). Kaplan-Meier-based mortality estimates were compared by stage. RESULTS: Overall, 6924 women were included (median age 53 years); 45.2% were diagnosed with ER+/PR+/HER2- tumors, 26.2% with HER2+ tumors, and 17.1% with ER-/PR-/HER2- tumors. Median follow-up time was 5 years (interquartile range 2.95-5.00). PS significantly improved predictive performance (C-index 0.721) for overall survival compared with AS (0.700) (p = 0.020). Kaplan-Meier hazard estimates suggested PS did not distinguish mortality risk between patients with IIB and IIIA or IB and IIA disease. CONCLUSIONS: PS has significantly improved predictive performance for OS compared with AS. As systemic therapies evolve, it will be important to re-evaluate the prognostic staging system, particularly for patients with intermediate-stage cancers. CLINICALTRIALS: gov Identifier: NCT02171078.

Rheumatology High Blood Pressure Protocol Reduces Disparities, But Delays Remain for External Primary Care.

BACKGROUND/OBJECTIVE: To address high blood pressure (BP) in rheumatology patients, we previously implemented BP Connect, a brief staff-driven protocol to address high BP. Although timely follow-up and hypertension rates improved for patients with in-system primary care (PC), many receive PC and rheumatology care in separate health systems. In this cohort study, we compared rates of timely PC follow-up for high BP across-system health maintenance organizations (HMOs) before and after BP Connect implementation. METHODS: All adult patients with high rheumatology clinic BP and PC in that HMO were eligible. BP Connect's protocol engaged the staff in remeasuring high BP (≥140/90 mm Hg), advising cardiovascular disease risk, and connecting timely PC follow-up, which for patients with PC across system includes written follow-up instructions. After an eligible rheumatology visit, the next HMO PC visit with BP was used to determine rates and odds of timely follow-up before and after using multivariable logistic regression. RESULTS: Across 1327 rheumatology visits with high BP and across-system PC (2013-2019), 951 occurred after 2015 BP Connect implementation; 400 had confirmed high BP. Primary care follow-up rose from 20.5% to 23.5%. The odds of timely PC BP follow-up insignificantly changed (odds ratio, 1.19; confidence interval, 0.85-1.68). For visits with Black patients, the odds of timely follow-up did significantly increase (1.95; confidence interval, 1.02-3.79). CONCLUSIONS: Timely follow-up for Black patients did improve, highlighting protocol interventions for more equitable health care. In contrast to our prior in-system study, BP Connect did not significantly improve follow-up with an across-system PC, indicating a need for direct scheduling. Future directions include piloting direct across-system scheduling.

The influence of anatomic stage and receptor status on first recurrence for breast cancer within 5 years (AFT-01).

BACKGROUND: Risk-stratified follow-up guidelines that account for the absolute risk and timing of recurrence may improve the quality and efficiency of breast cancer follow-up. The objective of this study was to assess the relationship of anatomic stage and receptor status with timing of the first recurrence for patients with local-regional breast cancer and generate risk-stratified follow-up recommendations. METHODS: The authors conducted a secondary analysis of 8007 patients with stage I-III breast cancer who enrolled in nine Alliance legacy clinical trials from 1997 to 2013 (ClinicalTrials.gov identifier NCT02171078). Patients who received standard-of-care therapy were included. Patients who were missing stage or receptor status were excluded. The primary outcome was days from the earliest treatment start date to the date of first recurrence. The primary explanatory variable was anatomic stage. The analysis was stratified by receptor type. Cox proportional-hazards regression models produced cumulative probabilities of recurrence. A dynamic programming algorithm approach was used to optimize the timing of follow-up intervals based on the timing of recurrence events. RESULTS: The time to first recurrence varied significantly between receptor types (p < .0001). Within each receptor type, stage influenced the time to recurrence (p < .0001). The risk of recurrence was highest and occurred earliest for estrogen receptor (ER)-negative/progesterone receptor (PR)-negative/Her2neu-negative tumors (stage III; 5-year probability of recurrence, 45.5%). The risk of recurrence was lower for ER-positive/PR-positive/Her2neu-positive tumors (stage III; 5-year probability of recurrence, 15.3%), with recurrences distributed over time. Model-generated follow-up recommendations by stage and receptor type were created. CONCLUSIONS: This study supports considering both anatomic stage and receptor status in follow-up recommendations. The implementation of risk-stratified guidelines based on these data has the potential to improve the quality and efficiency of follow-up.

Identifying Young Adults at High Risk for Weight Gain Using Machine Learning.

INTRODUCTION: Weight gain among young adults continues to increase. Identifying adults at high risk for weight gain and intervening before they gain weight could have a major public health impact. Our objective was to develop and test electronic health record-based machine learning models to predict weight gain in young adults with overweight/class 1 obesity. METHODS: Seven machine learning models were assessed, including three regression models, random forest, single-layer neural network, gradient-boosted decision trees, and support vector machine (SVM) models. Four categories of predictors were included: 1) demographics; 2) obesity-related health conditions; 3) laboratory data and vital signs; and 4) neighborhood-level variables. The cohort was split 60:40 for model training and validation. Area under the receiver operating characteristic curves (AUC) were calculated to determine model accuracy at predicting high-risk individuals, defined by ≥ 10% total body weight gain within 2 y. Variable importance was measured via generalized analysis of variance procedures. RESULTS: Of the 24,183 patients (mean [SD] age, 32.0 [6.3] y; 55.1% females) in the study, 14.2% gained ≥10% total body weight. Area under the receiver operating characteristic curves varied from 0.557 (SVM) to 0.675 (gradient-boosted decision trees). Age, sex, and baseline body mass index were the most important predictors among the models except SVM and neural network. CONCLUSIONS: Our machine learning models performed similarly and had modest accuracy for identifying young adults at risk of weight gain. Future models may need to incorporate behavioral and/or genetic information to enhance model accuracy.

Barriers to breast reconstruction for socioeconomically disadvantaged women.

PURPOSE: Socioeconomic disparities in post-mastectomy breast reconstruction exist. Key informants have suggested that finding providers who accept Medicaid insurance and longer travel time to a plastic surgeon are important barriers. Our objective was to assess the relationship between these factors and reconstruction for socioeconomically disadvantaged women in Wisconsin. METHODS: We identified women < 75 years of age with stage 0-III breast cancer who underwent mastectomy using the Wisconsin Cancer Reporting System. Women in the most disadvantaged state-based tertile of the Area Deprivation Index were included (n = 1809). Geocoding determined turn-by-turn drive time from women's address to the nearest accredited Commission on Cancer or National Accreditation Program for Breast Centers. Multivariable logistic regression determined the relationship between reconstruction, Medicaid, and travel time, controlling for patient factors known to impact reconstruction. Average adjusted predicted probabilities of receiving reconstruction were calculated. RESULTS: Most patients had early-stage breast cancer (51% stage 0/I) and 15.2% had Medicaid. 37% of women underwent reconstruction. Socioeconomically disadvantaged women with Medicaid (OR = 0.62, 95% CI 0.46-0.84) and longer travel times (OR = 0.99, 95% CI 0.99-1.0) were less likely to receive reconstruction. Patients with the lowest predicted probability of reconstruction were those with Medicaid who lived furthest from a plastic surgeon. CONCLUSION: Among socioeconomically disadvantaged women, Medicaid and travel remained associated with lower rates of reconstruction. Further work will explore opportunities to improve access to reconstruction for women with Medicaid. This is particularly challenging as it may require socioeconomically disadvantaged women to travel further to receive care.

Obesity and "obesity-related" cancers: are there body mass index cut-points?

BACKGROUND: Despite compelling links between excess body weight and cancer, body mass index (BMI) cut-points, or thresholds above which cancer incidence increased, have not been identified. The objective of this study was to determine if BMI cut-points exist for 14 obesity-related cancers. SUBJECTS/METHODS: In this retrospective cohort study, patients 18-75 years old were included if they had ≥2 clinical encounters with BMI measurements in the electronic health record (EHR) at a single academic medical center from 2008 to 2018. Patients who were pregnant, had a history of cancer, or had undergone bariatric surgery were excluded. Adjusted logistic regression was performed to identify cancers that were associated with increasing BMI. For those cancers, BMI cut-points were calculated using adjusted quantile regression for cancer incidence at 80% sensitivity. Logistic and quantile regression models were adjusted for age, sex, race/ethnicity, and smoking status. RESULTS: A total of 7079 cancer patients (mean age 58.5 years, mean BMI 30.5 kg/m2) and 270,441 non-cancer patients (mean age 43.8 years, mean BMI 28.8 kg/m2) were included in the study. In adjusted logistic regression analyses, statistically significant associations were identified between increasing BMI and the incidence of kidney, thyroid, and uterine cancer. BMI cut-points were identified for kidney (26.3 kg/m2) and uterine (26.9 kg/m2) cancer. CONCLUSIONS: BMI cut-points that accurately predicted development kidney and uterine cancer occurred in the overweight category. Analysis of multi-institutional EHR data may help determine if these relationships are generalizable to other health care settings. If they are, incorporation of BMI into the screening algorithms for these cancers may be warranted.

Treatment of carotid stenosis in asymptomatic, nonoctogenarian, standard risk patients with stenting versus endarterectomy trials.

OBJECTIVE: Asymptomatic carotid stenosis is the most frequent indication for carotid endarterectomy (CEA) in the United States. Published trials and guidelines support CEA indications in selected patients with longer projected survival and when periprocedural complications are low. Transfemoral carotid artery stenting with embolic protection (CAS) is a newer treatment option. The objective of this study was to compare outcomes in asymptomatic, nonoctogenarian patients treated with CAS vs CEA. METHODS: Patient-level data was analyzed from 2544 subjects with ≥70% asymptomatic carotid stenosis who were randomized to CAS or CEA in addition to standard medical therapy. One trial enrolled 1091 (548 CAS, 543 CEA) and another enrolled 1453 (1089 CAS, 364 CEA) asymptomatic patients less than 80 years old (upper age eligibility). Independent neurologic assessment and routine cardiac enzyme screening were performed. The prespecified, primary composite endpoint was any stroke, myocardial infarction, or death during the periprocedural period or ipsilateral stroke within 4 years after randomization. RESULTS: There was no significant difference in the primary endpoint between CAS and CEA (5.3% vs 5.1%; hazard ratio, 1.02; 95% confidence interval, 0.7-1.5; P = .91). Periprocedural rates for the components are (CAS vs CEA): any stroke (2.7% vs 1.5%; P = .07), myocardial infarction (0.6% vs 1.7%; P = .01), death (0.1% vs 0.2%; P = .62), and any stroke or death (2.7% vs 1.6%; P = .07). After this period, the rates of ipsilateral stroke were similar (2.3% vs 2.2%; P = .97). CONCLUSIONS: In a pooled analysis of two large randomized trials of CAS and CEA in asymptomatic, nonoctogenarian patients, CAS achieves comparable short- and long-term results to CEA.

Analysis of the Impact of the COVID-19 Pandemic on the Multidisciplinary Management of Breast Cancer: Review from the American Society of Breast Surgeons COVID-19 and Mastery Registries.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic has resulted in rapid and regionally different approaches to breast cancer care. METHODS: In order to evaluate these changes, a COVID-19-specific registry was developed within the American Society of Breast Surgeons (ASBrS) Mastery that tracked whether decisions were usual or modified for COVID-19. Data on patient care entered into the COVID-19-specific registry and the ASBrS Mastery registry from 1 March 2020 to 15 March 2021 were reviewed. RESULTS: Overall, 177 surgeons entered demographic and treatment data on 2791 patients. Mean patient age was 62.7 years and 9.0% (252) were of African American race. Initial consultation occurred via telehealth in 6.2% (173) of patients and 1.4% (40) developed COVID-19. Mean invasive tumor size was 2.1 cm and 17.8% (411) were node-positive. In estrogen receptor-positive/human epidermal growth factor receptor 2-negative (ER+/HER2-) disease, neoadjuvant endocrine therapy (NET) was used as the usual approach in 6.9% (119) of patients and due to COVID-19 in an additional 31% (542) of patients. Patients were more likely to receive NET due to COVID-19 with increasing age and if they lived in the Northeast or Southeast (odds ratio [OR] 1.1, 2.3, and 1.7, respectively; p < 0.05). Genomic testing was performed on 51.5% (781) of estrogen-positive patients, of whom 20.7% (162) had testing on the core due to COVID-19. Patients were less likely to have core biopsy genomic testing due to COVID-19 if they were older (OR 0.89; p = 0.01) and more likely if they were node-positive (OR 4.0; p < 0.05). A change in surgical approach due to COVID-19 was reported for 5.4% (151) of patients. CONCLUSION: The ASBrS COVID-19 registry provided a platform for monitoring treatment changes due to the pandemic, highlighting the increased use of NET.

Regularized Ordinal Regression and the ordinalNet R Package.

Regularization techniques such as the lasso (Tibshirani 1996) and elastic net (Zou and Hastie 2005) can be used to improve regression model coefficient estimation and prediction accuracy, as well as to perform variable selection. Ordinal regression models are widely used in applications where the use of regularization could be beneficial; however, these models are not included in many popular software packages for regularized regression. We propose a coordinate descent algorithm to fit a broad class of ordinal regression models with an elastic net penalty. Furthermore, we demonstrate that each model in this class generalizes to a more flexible form, that can be used to model either ordered or unordered categorical response data. We call this the elementwise link multinomial-ordinal (ELMO) class, and it includes widely used models such as multinomial logistic regression (which also has an ordinal form) and ordinal logistic regression (which also has an unordered multinomial form). We introduce an elastic net penalty class that applies to either model form, and additionally, this penalty can be used to shrink a non-ordinal model toward its ordinal counterpart. Finally, we introduce the R package ordinalNet, which implements the algorithm for this model class.

Breast Cancer Outcomes of Neoadjuvant Versus Adjuvant Chemotherapy by Receptor Subtype: A Scoping Review.

BACKGROUND: Trials demonstrate equivalent survival for breast cancers treated with neoadjuvant chemotherapy (NAC) or adjuvant chemotherapy (AC). However, these were conducted before the recognition of the importance of receptor subtype for survival and chemotherapy response. Therefore, chemotherapy timing may impact survival for certain receptor subtypes. A scoping review of studies assessing outcomes by chemotherapy timing based on receptor subtype was conducted to evaluate gaps in the existing literature. METHODS: Three databases were searched in February 2019 with terms related to breast cancer, NAC/AC, and survival. Inclusion criteria were original peer-reviewed studies published in English after 1989 comparing breast cancer outcomes for females based on chemotherapy timing. Studies/sections of studies lacking outcomes by receptor subtype or including patients missing appropriate targeted therapy were excluded. RESULTS: Of 7354 articles, 262 abstracts and 60 full texts were reviewed. Three studies met criteria. All were single-institution retrospective studies analyzing outcomes for triple negative (TN) patients with one study also examining luminal A patients. Significant differences in clinical characteristics existed between patients selected for NAC versus AC. Two studies demonstrated no survival difference by chemotherapy timing for TN patients, with the third showing improved likelihood of survival after AC for TN patients. No difference was seen for patients with luminal A cancer. CONCLUSIONS: Our scoping review reveals a significant gap in the existing literature regarding optimal timing of chemotherapy for modern-era patients receiving targeted therapy based on receptor subtype. Review of the identified studies identified methodological challenges to answering this question through observational study designs.

Safety of Antithymocyte Globulin in Patients Undergoing Liver Transplantation With Livers From Donation After Circulatory Death Donors.

Background: Studies suggest that rabbit-antithymocyte globulin (rATG) decreases biliary complications (BCs) after donation-after-circulatory-death-donor liver transplantation (DCD LTx), but safety data are lacking. Objective: Our aim was to assess the safety of rATG for this indication. The secondary end point was efficacy of rATG for this indication. Methods: Adult recipients of DCD LTx were divided into 2 cohorts: protocolized use of rATG in the modern era (July 1, 2013, to December 31, 2016) and a historical control without rATG (January 1, 2005, to June 30, 2013). Incidence of infection, leukopenia, and thrombocytopenia were compared for the safety assessment, incidence of BCs, ischemic cholangiopathy (IC), and transplant outcomes for the efficacy assessment. Results: A total of 83 patients met inclusion criteria: 42 in the historical cohort and 41 in the modern cohort. The modern cohort had significantly fewer bacterial infections at 3 months (historical 54.8% vs modern 23%; P = 0.004) and 1 year (historical 62.1% vs modern 34.2%, P = 0.004). The modern cohort also had fewer fungal infections at these time points (historical 33.3% and 47.9% vs modern 15% and 15%; P = 0.001). There were no significant differences in platelet or white blood cell reduction between groups. There was a nonsignificant, but numerical, trend toward reduced IC/BC in the modern cohort at 1 year (IC: historical 30.1% vs modern 13.2%, P = 0.08; BC: historical 51% vs modern 37.5%, P = 0.13). There was no difference in graft/patient survival. Conclusion and Relevance: Our data suggest no major safety issues with rATG in DCD LTx. Our study should ease clinical apprehension surrounding rATG use for this indication. Future prospective studies are needed to further evaluate the role of rATG and its impact on efficacy end points.

Genetic inhibition of autophagy in a transgenic mouse model of anal cancer.

BACKGROUND: The dynamic role of autophagy in cancer development is a topic of considerable research and debate. Previously published studies have shown that anal cancer development can be promoted or prevented with the pharmacologic inhibition or induction, respectively, of autophagy in a human papillomavirus (HPV) mouse model. However, these results are confounded by the fact that the drugs utilized are known to affect other pathways besides autophagy. It has also been shown that autophagic inhibition occurs in the setting of HPV16 oncoprotein expression (E6 and E7) and correlates with increased susceptibility to anal carcinogenesis. MATERIALS AND METHODS: In this study, we employed a conditional, genetic, autophagic (Atg7) knockout mouse model to determine conclusively that autophagy has a role in anal cancer development, in the absence or presence of E6 and E7. RESULTS: In mice lacking both HPV16 oncogenes, knockout of autophagy followed by exposure to a carcinogen resulted in a tumor incidence of 40%, compared to 0% in mice treated with a carcinogen alone with an intact autophagic pathway (P = 0.007). In mice expressing either one or both HPV16 oncoproteins, the addition of genetic knockout of autophagy to carcinogen treatment did not lead to a significant difference in tumor incidence compared to carcinogen treatment alone, consistent with the ability of HPV oncogenes to inhibit autophagy in themselves. CONCLUSIONS: These results provide the first conclusive evidence for the distinct role of autophagy in anal carcinogenesis, and suggest that autophagy is a plausible target for therapies aimed at reducing anal dysplasia and anal cancer development.

Estimation and testing problems in auditory neuroscience via clustering.

The processing of auditory information in neurons is an important area in neuroscience. We consider statistical analysis for an electrophysiological experiment related to this area. The recorded synaptic current responses from the experiment are observed as clusters, where the number of clusters is related to an important characteristic of the auditory system. This number is difficult to estimate visually because the clusters are blurred by biological variability. Using singular value decomposition and a Gaussian mixture model, we develop an estimator for the number of clusters. Additionally, we provide a method for hypothesis testing and sample size determination in the two-sample problem. We illustrate our approach with both simulated and experimental data.

Discrete mixture modeling to address genetic heterogeneity in time-to-event regression.

MOTIVATION: Time-to-event regression models are a critical tool for associating survival time outcomes with molecular data. Despite mounting evidence that genetic subgroups of the same clinical disease exist, little attention has been given to exploring how this heterogeneity affects time-to-event model building and how to accommodate it. Methods able to diagnose and model heterogeneity should be valuable additions to the biomarker discovery toolset. RESULTS: We propose a mixture of survival functions that classifies subjects with similar relationships to a time-to-event response. This model incorporates multivariate regression and model selection and can be fit with an expectation maximization algorithm, we call Cox-assisted clustering. We illustrate a likely manifestation of genetic heterogeneity and demonstrate how it may affect survival models with little warning. An application to gene expression in ovarian cancer DNA repair pathways illustrates how the model may be used to learn new genetic subsets for risk stratification. We explore the implications of this model for censored observations and the effect on genomic predictors and diagnostic analysis. AVAILABILITY AND IMPLEMENTATION: R implementation of CAC using standard packages is available at https://gist.github.com/programeng/8620b85146b14b6edf8f Data used in the analysis are publicly available.

Spatio-temporal in vivo recording of dCREB2 dynamics in Drosophila long-term memory processing.

CREB (cAMP response element-binding protein) is an evolutionarily conserved transcription factor, playing key roles in synaptic plasticity, intrinsic excitability and long-term memory (LTM) formation. The Drosophila homologue of mammalian CREB, dCREB2, is also important for LTM. However, the spatio-temporal nature of dCREB2 activity during memory consolidation is poorly understood. Using an in vivo reporter system, we examined dCREB2 activity continuously in specific brain regions during LTM processing. Two brain regions that have been shown to be important for Drosophila LTM are the ellipsoid body (EB) and the mushroom body (MB). We found that dCREB2 reporter activity is persistently elevated in EB R2/R4m neurons, but not neighboring R3/R4d neurons, following LTM-inducing training. In multiple subsets of MB neurons, dCREB2 reporter activity is suppressed immediately following LTM-specific training, and elevated during late windows. In addition, we observed heterogeneous responses across different subsets of neurons in MB αß lobe during LTM processing. All of these changes suggest that dCREB2 functions in both the EB and MB for LTM formation, and that this activity contributes to the process of systems consolidation.

Prognostic factors modifying the treatment-free interval in recurrent ovarian cancer.

OBJECTIVES: While primary treatment for high-grade serous ovarian cancer tends to be uniform - maximal debulking and platinum/taxane adjuvant chemotherapy - there is little standardization of treatment in the recurrent setting beyond the exhaustive use of platinum therapies. Using secondary data from multiple centers participating in the Cancer Genome Atlas study (TCGA), we seek to characterize clinical features, timing and serial response data to provide empirical evidence for treatment expectations in the recurrent setting. METHODS: We conducted a retrospective survival analysis of TCGA study primary and secondary patient chemotherapy regimens by characterizing the dynamics of 1119 lines of therapy comprising the treatment of 461 high-grade serous ovarian cancer patients. All patients with post-surgical drug therapy information from the TCGA database were included in this study. RESULTS: A complete response to adjuvant therapy led to longer overall survival, but did not affect treatment free intervals (TFIs) after relapse of disease. A strong predictor of the TFI on the next treatment regimen was the previous TFI with a decaying effect. The number of previous treatments, of platinum treatments, and the length of time from surgery all have an exponentially decreasing effect on TFI. Re-treatment times appear to cluster at predictable times following surgery. CONCLUSIONS: While patients experience a consistent reduction in TFI with increasing re-treatment, the initial adjuvant interval is unrelated to later interval lengths. Platinum re-treatment remained an effective option in patients typically thought to be platinum resistant and the timing of monitoring visits may drive overall re-treatment patterns.

Embedding an Education Intervention about Shared Decision Making into an RCT: Ensuring competency and fidelity.

Objective: To describe the outcomes of training nephrology clinicians and clinical research participants, to use the Best Case/Worst Case Communication intervention, for discussions about dialysis initiation for patients with life-limiting illness, during a randomized clinical trial to ensure competency, fidelity to the intervention, and adherence to study protocols and the intervention throughout the trial. Methods: We enrolled 68 nephrologists at ten study sites and randomized them to receive training or wait-list control. We collected copies of completed graphic aids (component of the intervention), used with study-enrolled patients, to measure fidelity and adherence. Results: We trained 34 of 36 nephrologists to competence and 27 completed the entire program. We received 60 graphic aids for study-enrolled patients for a 73% return rate in the intervention arm. The intervention fidelity score for the graphic aid reflected completion of all elements throughout the study. Conclusion: We successfully taught the Best Case/Worst Case Communication intervention to clinicians as research participants within a randomized clinical trial. Innovation: Decisions about dialysis are an opportunity to discuss prognosis and uncertainty in relation to consideration of prolonged life supporting therapy. Our study reveals a strategy to evaluate adherence to a communication intervention in real time during a clinical study.