tbuckley/cabot-search huggingface dataset:
Deep learning for lung cancer prognostication: A retrospective multi-cohort radiomics study
Authors: Ahmed Hosny, Chintan Parmar, Thibaud P. Coroller, Patrick Grossmann, Roman Zeleznik, Avnish Kumar, Johan Bussink, Robert J. Gillies, Raymond H. Mak, Hugo J. W. L. Aerts
Journal: PLoS Medicine (2018)

Non-small-cell lung cancer (NSCLC) patients often demonstrate varying clinical courses and outcomes, even within the same tumor stage. This study explores deep learning applications in medical imaging allowing for the automated quantification of radiographic characteristics and potentially improving patient stratification.We performed an integrative analysis on 7 independent datasets across 5 institutions totaling 1,194 NSCLC patients (age median = 68.3 years [range 32.5-93.3], survival median = 1.7 years [range 0.0-11.7]). Using external validation in computed tomography (CT) data, we identified prognostic signatures using a 3D convolutional neural network (CNN) for patients treated with radiotherapy (n = 771, age median = 68.0 years [range 32.5-93.3], survival median = 1.3 years [range 0.0-11.7]). We then employed a transfer learning approach to achieve the same for surgery patients (n = 391, age median = 69.1 years [range 37.2-88.0], survival median = 3.1 years [range 0.0-8.8]). We found that the CNN predictions were significantly associated with 2-year overall survival from the start of respective treatment for radiotherapy (area under the receiver operating characteristic curve [AUC] = 0.70 [95% CI 0.63-0.78], p < 0.001) and surgery (AUC = 0.71 [95% CI 0.60-0.82], p < 0.001) patients. The CNN was also able to significantly stratify patients into low and high mortality risk groups in both the radiotherapy (p < 0.001) and surgery (p = 0.03) datasets. Additionally, the CNN was found to significantly outperform random forest models built on clinical parameters-including age, sex, and tumor node metastasis stage-as well as demonstrate high robustness against test-retest (intraclass correlation coefficient = 0.91) and inter-reader (Spearman's rank-order correlation = 0.88) variations. To gain a better understanding of the characteristics captured by the CNN, we identified regions with the most contribution towards predictions and highlighted the importance of tumor-surrounding tissue in patient stratification. We also present preliminary findings on the biological basis of the captured phenotypes as being linked to cell cycle and transcriptional processes. Limitations include the retrospective nature of this study as well as the opaque black box nature of deep learning networks.Our results provide evidence that deep learning networks may be used for mortality risk stratification based on standard-of-care CT images from NSCLC patients. This evidence motivates future research into better deciphering the clinical and biological basis of deep learning networks as well as validation in prospective data.
Prevalence and usage patterns of opiates in patients with lung, breast, and head and neck cancer.
Authors: Kyle Andrew Westbrook, Chul Ahn, Saad A. Khan
Journal: Journal of Clinical Oncology (2018)

120 Background: Prescription opiate abuse is a declared public health emergency, involved in 17,536 deaths in 2015. We don’t know how many cancer patients died from prescription opiates and there is little published data about their prescribing patterns. Methods: Using the UTSW tumor registry, we analyzed all prescriptions for 6424 lung/breast/head and neck cancer patients undergoing therapy including radiation from 2009-2016; patient demographics, cancer information, treatment modality, concurrent medicines, substance abuse history, and survival. Chi-square tests were used to investigate if higher rates of opiate use were seen in those who receive chemotherapy, actively smoke or use alcohol, have head and neck cancer. Results: Opiate use was highly prevalent in cancer patients with 2902/4307 (67%) of women and 1597/2112 (76%) of men requiring opiates. Hydrocodone was the most common opiate at (out of 6424 total) 67%, followed by morphine 12%, fentanyl 9%, oxycodone 7% and hydromorphone 6%. Gabapentin was prescribed to 18.7% of women and 15.9% of men; 494/6424 (8%) patients had 3 or more different opiates prescribed; those who were given gabapentin had a higher rate of 3 or more opiates 249/1241 (20%). Those with current alcohol use required opiates 2001/2643 (76%) compared to those with no alcohol use 2101/3145 (67%) (p&lt;0.0001); while active smokers used opiates 1033/1366 (76%) compared to never smokers 1859/2815 (66%) (p&lt;0.0001). Head and neck patients at 1529/1982 (77%) had higher opiate use than those with breast 1913/2932 (65%) or lung cancer 1061/1510 (70%) (p&lt;0.0001). Patients receiving chemotherapy with their radiation required opiates 696/850 (82%) compared to those who got no chemotherapy 3807/5574 (68%) (p&lt;0.0001). In patients with a radiation course lasting &gt;4 weeks, 8.8% received opiates 12 months after completion of their therapy. Conclusions: More than 70% of cancer patients use opiates after radiation; significantly higher rates of opiate use are seen in those who receive chemotherapy, actively smoke, use alcohol, or have head and neck cancer. Patients treated with radiation for &gt;4 weeks have high rates of opiate use a year after treatment completion.
PCSK9 — A Journey to Cardiovascular Outcomes
Authors: John R Burnett, Amanda J Hooper
Journal: New England Journal of Medicine (2018)

Some patients do not reach target low-density lipoprotein (LDL) cholesterol levels despite receiving treatment with high-intensity statins. Monoclonal antibodies that inhibit proprotein convertase subtilisin–kexin type 9 (PCSK9) have emerged as an effective treatment to address this gap and can lower LDL cholesterol by approximately 60% among patients who are already receiving standard therapy.1,2 PCSK9 is secreted by the liver and is found in 1 in every 500 LDL particles in the circulation. When these PCSK9-associated particles bind to the LDL receptor, the complex is internalized and the receptor is targeted for degradation rather than recycling back to the cell surface.3 . . .
Characterising risk of in-hospital mortality following cardiac arrest using machine learning: A retrospective international registry study
Authors: Shane Nanayakkara, Sam Fogarty, Michael Tremeer, Kelvin Ross, Brent Richards, Christoph Bergmeir, Sheng Xu, Dion Stub, Karen Smith, Mark Tacey, Danny Liew, David Pilcher, David M. Kaye
Journal: PLoS Medicine (2018)

Resuscitated cardiac arrest is associated with high mortality; however, the ability to estimate risk of adverse outcomes using existing illness severity scores is limited. Using in-hospital data available within the first 24 hours of admission, we aimed to develop more accurate models of risk prediction using both logistic regression (LR) and machine learning (ML) techniques, with a combination of demographic, physiologic, and biochemical information.Patient-level data were extracted from the Australian and New Zealand Intensive Care Society (ANZICS) Adult Patient Database for patients who had experienced a cardiac arrest within 24 hours prior to admission to an intensive care unit (ICU) during the period January 2006 to December 2016. The primary outcome was in-hospital mortality. The models were trained and tested on a dataset (split 90:10) including age, lowest and highest physiologic variables during the first 24 hours, and key past medical history. LR and 5 ML approaches (gradient boosting machine [GBM], support vector classifier [SVC], random forest [RF], artificial neural network [ANN], and an ensemble) were compared to the APACHE III and Australian and New Zealand Risk of Death (ANZROD) predictions. In all, 39,566 patients from 186 ICUs were analysed. Mean (±SD) age was 61 ± 17 years; 65% were male. Overall in-hospital mortality was 45.5%. Models were evaluated in the test set. The APACHE III and ANZROD scores demonstrated good discrimination (area under the receiver operating characteristic curve [AUROC] = 0.80 [95% CI 0.79-0.82] and 0.81 [95% CI 0.8-0.82], respectively) and modest calibration (Brier score 0.19 for both), which was slightly improved by LR (AUROC = 0.82 [95% CI 0.81-0.83], DeLong test, p < 0.001). Discrimination was significantly improved using ML models (ensemble and GBM AUROCs = 0.87 [95% CI 0.86-0.88], DeLong test, p < 0.001), with an improvement in performance (Brier score reduction of 22%). Explainability models were created to assist in identifying the physiologic features that most contributed to an individual patient's survival. Key limitations include the absence of pre-hospital data and absence of external validation.ML approaches significantly enhance predictive discrimination for mortality following cardiac arrest compared to existing illness severity scores and LR, without the use of pre-hospital data. The discriminative ability of these ML models requires validation in external cohorts to establish generalisability.
A novel tumor cell therapy using Th1 cells: The critical role of APC/Th1 cell-cell interaction for the initiation of antitumor immunity in vivo
Authors: Takashi Nishimura, Kenji Chamoto, Takemasa Tsuji
Journal: Cancer Research (2004)

5451  The introduction of local help, which can overcome immunosuppression of tumor-bearing host, is essential for developing antigen-specific tumor immunotherapy. To introduce local help, we have investigated the adoptive tumor immunotherapy using Th1 cells or Th1 cytokine-conditioned bone marrow-derived dendritic cells (BMDC1). The adoptive transfer of OVA-specific Th1 cells (over 2x107) into tumor-bearing mice caused a complete regression of tumor mass of A20-OVA which were A20 B lymphoma cells transfected with OVA gene as a model tumor antigen. For successful Th1-cell therapy, host CD8+T cells were essential in addition to Th1 cells. Thus, Th1/Tc1 circuit appears to be important for complete rejection of tumor by Th1 cell therapy. To induce Th1-dominant antitumor immunity in A20-OVA-bearing mice, we also tried to apply OVA-pulsed BMDC1, which were preferable for inducing antigen-specific Th1 and Tc1 cells, to adoptive tumor immunotherapy. Vaccination of A20-OVA-bearing mice with intradermal injection of inactivated A20-OVA, OVA pulsed-BMDC1 or Th1 cells (5x106) alone showed no significant antitumor effect in vivo. However, combined vaccination therapy with OVA-pulsed BMDC1, A20-OVA and Th1 cells caused a complete regression of tumor mass. Thus, Th1 cells were demonstrated to augment BMDC1-based tumor vaccination therapy in vivo. Finally, we have succeeded to cure mice bearing with MHC class II-negative EG-7 tumor cells using Th1-cell therapy. Using this model, we demonstrated that APC/Th1 cell-cell interaction and Th1 cell expansion in draininig lymph node is essential for the induction of tetramer-positive tumor specific CTL and complete regression of tumor. We also succeeded in generation of tumor-specific human Th1 cells. Therefore, Th1-cell therapy will provide a new strategy for tumor cell therapy in future.
Primary Mediastinal B-Cell Lymphoma: Evaluation of Clinicopathologic Diagnosis Compared to Gene Expression Based Diagnosis in a Clinical Trial with CD30+ B-Cell Lymphomas
Authors: Jakub Svoboda, Steven M. Bair, Christian Steidl, Marco Ruella, Daniel J. Landsburg, Sunita Dwivedy Nasta, Stefan Klaus Barta, M. Reza Nejati, James Nathan Gerson, Lauren Elizabeth Strelec, Matthew R. Youngman, Elise A. Chong, Olga Kutovaya, Stacy Hung, Agata M. Bogusz, Megan S. Lim, Stephen J. Schuster
Journal: Blood (2018)
The association between physical functioning, symptom burden, and coping strategies with quality of life (QOL) in patients with chronic graft-versus-host disease (cGVHD).
Authors: Robert Sommer, Jamie M. Jacobs, Lauren Waldman, Lara Traeger, Joseph Greer, Julie Vanderklish, Yi-Bin Albert Chen, Thomas R. Spitzer, Jennifer S. Temel, Areej El-Jawahri
Journal: Journal of Clinical Oncology (2018)

178 Background: Allogeneic stem cell transplant survivors with cGVHD experience substantial psychological distress and impairments in QOL. However, the relationship between patients’ physical functioning, symptom burden, coping strategies, and QOL over time is unknown. Methods: We conducted a longitudinal study of patients with moderate-severe cGVHD. We assessed patient-reported psychological distress (Hospital Anxiety and Depression Scale), QOL (Functional Assessment of Cancer Therapy-General), physical functioning (Human Activity Profile), cGVHD symptom burden (Lee Symptom Scale), and coping (Coping Inventory for Stressful Situations) at baseline, 3 months, and 6 months. Using mixed linear effects models, we examined the longitudinal relationship between QOL and physical functioning, cGVHD symptoms, and coping strategies. Results: We enrolled 53 patients with moderate (71.7%, 38/53) or severe (28.3%, 15/53) cGVHD. The rate of clinically significant depression and anxiety symptoms at baseline was 32.1% (17/53) and 30.2% (16/33), respectively, and did not change over time. Patients reported low QOL at baseline [M = 70.33, SD = 18.96], which did not change significantly over time [β = -0.66, SE = 1.11, P = 0.550]. Over time, higher physical functioning was associated with better QOL [β = 0.17, SE = 0.05, P = 0.001], while greater symptom burden was associated with worse QOL [β = -0.38, SE = 0.06, P &lt; 0.001]. While the use of emotion-oriented coping was associated with lower QOL over time [β = -0.70, SE = 0.14, P &lt; 0.001], the use of avoidance-oriented coping was associated with higher QOL over time [β = 0.38, SE = 0.10, P &lt; 0.001]. Task-oriented coping was not associated with psychological distress or QOL. Conclusions: Patients with moderate-severe cGVHD report substantial psychological distress and persistently impaired QOL over time. Higher physical function and lower symptom burden are associated with improved QOL. The use of certain coping strategies was associated with changes in QOL. These data underscore the need for supportive care interventions to promote effective coping and enhance physical functioning in patients with cGVHD.
Attenuation of breast cancer risk in benign breast disease
Authors: Alyssa Bottrell, Alissa Kapke, Mei Lu, Sandra Wolman, Maria Worsham
Journal: Cancer Research (2008)

3859  Background: Benign breast disease is a common condition in women. Much research has been devoted to studying benign breast disease (BBD) lesions to investigate how these lesions alter a woman’s risk of developing breast cancer (BC). In a Detroit-based multi-ethnic cohort of women with biopsy-proven BBD we observed that fibrosis and fibroadenoma were protective against BC progression from BBD.  Methods: To further dissect out the attenuation of risk conferred by fibroadenoma, these lesions were investigated with respect to lesion size and degree and type of epithelial proliferation in a case-control (1:3 match) cohort of 872 women nested within the parent cohort of 4,970 women with BBD.  Results: In the parent cohort, fibrosis was shown to attenuate the risk of developing breast cancer. The risk of developing breast cancer was 37% lower among women with fibrosis compared to those without fibrosis (RR: 0.63; 95% CI 0.45, 0.87; p=0.0053) after adjusting for other parameters. In the nested case-control study, fibroadenoma was shown to attenuate the risk of progression to breast cancer. The odds of breast cancer was reduced by 35% in women with fibroadenoma compared to those without fibroadenoma (OR: 0.65; 95% CI: 0.46, 0.94; p=0.02) after adjusting for other parameters. This reduction in risk of breast cancer was seen regardless of whether the fibroadenoma was proliferative or nonproliferative. In addition, the size of the fibroadenoma was found to be inversely related to breast cancer risk. The average size of fibroadenoma was 1.14 cm (std =0.76) in women who developed breast cancer versus 1.56 cm (std =1.196) in women who did not progress to breast cancer (p=0.0002). Also, the size of the fibroadenoma was found to be inversely related to the degree and type of epithelial proliferation of the associated fibroadenoma. Nonproliferative fibroadenomas were on average larger in size than proliferative fibroadenomas which tended to be larger than fibroadenomas associated with atypical hyperplasia.  Conclusion: Stromal elements are shared features among fibrosis and fibroadenoma lesions. Women with a diagnosis of fibrosis in the parent cohort had an attenuated risk of progression to breast cancer. Also, in the nested case-control study, women with fibroadenoma were less likely to develop breast cancer. Fibroadenoma size was associated with type and degree of epithelial proliferation and breast cancer risk.  Support: NIH CA 70923
Uptake and Tracer Kinetic of O-(2-(18)F-fluoroethyl)-L-Tyrosine in Meningioma
Authors: Victor Basse, Gurvan Dissaux, Romuald Seizeur, David Bourhis, Solène Querellou
Journal: Clinical Nuclear Medicine (2018)

F-fluoroethyltyrosine (FET) is a well-established PET tracer for the imaging of cerebral gliomas. Recent studies reported interest in meningiomas. A study published by Cornelius et al concludes that FET PET may provide additional information for noninvasive grading of meningiomas. Indeed, the combination of tumor background ratio with a cutoff value of 2.3 associated with time activity curve pattern slightly improved the differentiation of high-grade from low-grade meningiomas (accuracy, 92%; P = 0.001). We present the case of a 75-year-old man that underlined the need to confirm the performance of these tools (curve pattern, tumor background ratios) to characterize meningiomas.
Targeting the proteostasis network in Huntington’s disease
Authors: Tânia R. Soares, Sara D. Reis, Brígida R. Pinho, Michael R. Duchen, Jorge M.A. Oliveira
Journal: Ageing Research Reviews (2018)

Huntington's disease (HD) is an autosomal dominant neurodegenerative disorder caused by a polyglutamine expansion mutation in the huntingtin protein. Expansions above 40 polyglutamine repeats are invariably fatal, following a symptomatic period characterised by choreiform movements, behavioural abnormalities, and cognitive decline. While mutant huntingtin (mHtt) is widely expressed from early life, most patients with HD present in mid-adulthood, highlighting the role of ageing in disease pathogenesis. mHtt undergoes proteolytic cleavage, misfolding, accumulation, and aggregation into inclusion bodies. The emerging model of HD pathogenesis proposes that the chronic production of misfolded mHtt overwhelms the chaperone machinery, diverting other misfolded clients to the proteasome and the autophagy pathways, ultimately leading to a global collapse of the proteostasis network. Multiple converging hypotheses also implicate ageing and its impact in the dysfunction of organelles as additional contributing factors to the collapse of proteostasis in HD. In particular, mitochondrial function is required to sustain the activity of ATP-dependent chaperones and proteolytic machinery. Recent studies elucidating mitochondria-endoplasmic reticulum interactions and uncovering a dedicated proteostasis machinery in mitochondria, suggest that mitochondria play a more active role in the maintenance of cellular proteostasis than previously thought. The enhancement of cytosolic proteostasis pathways shows promise for HD treatment, protecting cells from the detrimental effects of mHtt accumulation. In this review, we consider how mHtt and its post translational modifications interfere with protein quality control pathways, and how the pharmacological and genetic modulation of components of the proteostasis network impact disease phenotypes in cellular and in vivo HD models.
Family perspectives on prognostic communication in the palliative oncology clinic: "Someone was kind enough to just tell me".
Authors: Kevin Craig, Karla T. Washington
Journal: Journal of Clinical Oncology (2018)

24 Background: Talking with patients with cancer and their families about the likely course of a disease is commonly cited as one of the most difficult aspects of healthcare delivery, yet palliative care providers routinely engage in such discussions. As such, attention to communication about prognosis in palliative oncology care has increased in recent years. Research and practice wisdom alike have provided important insights into the experiences of providers, patients, and family members who have taken part in discussions about prognosis and, relatedly, goals of care. As a result, we now have a number of highly effective tools at our disposal to enhance prognostic communication in palliative care. Methods: We sought to build on this existing expertise, applying a social ecological perspective to the study of prognostic communication from the family caregiver’s point of view. In this session, we present the findings of an inductive thematic analysis of qualitative data collected as part of randomized clinical trial of a family caregiver intervention in palliative oncology (R21CA191165; Principal Investigator: Author). Results: Findings illustrate how family caregivers ( N = 63) experience discussions about prognosis as one part of a much larger experience with the healthcare system. Themes describe how family caregivers attempt to make sense of seemingly contradictory information, incorporate information from non-provider sources, elicit prognostic information when it is not forthcoming, make their information needs known when they conflict with the patient’s, and use information to plan their future lives. Conclusions: Evidence-informed strategies to improve communication with family caregivers as vital partners in the delivery of palliative oncology care are sorely needed. Clinical trial information: NCT02427490.
Chemogenetic silencing of hippocampal neurons suppresses epileptic neural circuits
Authors: Qi-Gang Zhou, Ashley D. Nemes, Daehoon Lee, Eun Jeoung Ro, Jing Zhang, Amy S. Nowacki, Susan M. Dymecki, Imad M. Najm, Hoonkyo Suh
Journal: Journal of Clinical Investigation (2018)

We investigated how pathological changes in newborn hippocampal dentate granule cells (DGCs) lead to epilepsy. Using a rabies virus-mediated retrograde tracing system and a designer receptors exclusively activated by designer drugs (DREADD) chemogenetic method, we demonstrated that newborn hippocampal DGCs are required for the formation of epileptic neural circuits and the induction of spontaneous recurrent seizures (SRS). A rabies virus-mediated mapping study revealed that aberrant circuit integration of hippocampal newborn DGCs formed excessive de novo excitatory connections as well as recurrent excitatory loops, allowing the hippocampus to produce, amplify, and propagate excessive recurrent excitatory signals. In epileptic mice, DREADD-mediated-specific suppression of hippocampal newborn DGCs dramatically reduced epileptic spikes and SRS in an inducible and reversible manner. Conversely, specific activation of hippocampal newborn DGCs increased both epileptic spikes and SRS. Our study reveals an essential role for hippocampal newborn DGCs in the formation and function of epileptic neural circuits, providing critical insights into DGCs as a potential therapeutic target for treating epilepsy.
Dolutegravir in sub-Saharan Africa: context is crucial
Authors: Jienchi Dorward, Raph L Hamers
Journal: The Lancet HIV (2018)

A new, low-cost, generic, fixed-dose antiretroviral therapy (ART) combination containing tenofovir, lamivudine, and dolutegravir is being introduced in many countries in sub-Saharan Africa.1 In The Lancet HIV, Andrew Phillips and colleagues2 address two important concerns regarding the rollout of this regimen. First, what are the overall risks and benefits of use in women of child bearing potential, given that there is a possible increased risk of neural tube defects?3 Second, what are the risks of functional dolutegravir monotherapy in those who already have resistance to tenofovir and lamivudine4 if people on ART are transitioned to tenofovir, lamivudine, and dolutegravir without confirmation of viral suppression? The authors used the HIV Synthesis Model to compare policy scenarios in a hypothetical southern African population.