Surveillance of Patients Following Primary Therapy

ABSTRACT During World War I, the 1918 influenza pandemic struck the fatigued combat troops serving on the Western Front. Medical treatment options were limited; thus, skilled military nursing care was the primary therapy and the best indicator of patient outcomes. This article examines the military nursing’s role in the care of the soldiers during the 1918 flu pandemic and compares this to the 2019 coronavirus pandemic.

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Trends in risk classification at diagnosis and choice of primary therapy for prostate cancer: An analysis of 10 839 patients from the Nara Urological Research and Treatment Group registry between 2004 and 2015

International Journal of Urology ◽

10.1111/iju.14666 ◽

2021 ◽

Author(s):

Yasushi Nakai ◽

Nobumichi Tanaka ◽

Tomomi Fujii ◽

Makito Miyake ◽

Satoshi Anai ◽

...

Keyword(s):

Prostate Cancer ◽

Treatment Group ◽

Risk Classification ◽

Primary Therapy

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Recurrence and Coniglobus Volumetric Resolution of Subacute and Chronic Subdural Hematoma Post-Middle Meningeal Artery Embolization

Diagnostics ◽

10.3390/diagnostics11020257 ◽

2021 ◽

Vol 11 (2) ◽

pp. 257

Author(s):

Ambooj Tiwari ◽

Adam A. Dmytriw ◽

Ryan Bo ◽

Nathan Farkas ◽

Phillip Ye ◽

...

Keyword(s):

Subdural Hematoma ◽

Chronic Subdural Hematoma ◽

Middle Meningeal Artery ◽

Volumetric Analysis ◽

Primary Therapy ◽

Curative Therapy ◽

Complete Obliteration ◽

Embolization Treatment ◽

Long Term Follow Up ◽

Meningeal Artery

Objective: To study the efficacy of middle meningeal artery (MMA) embolization for the treatment of chronic subdural hematoma (SDH) and characterize its post-embolization volumetric resolution. Methods: Ten patients diagnosed with 13 cSDH underwent MMA embolization. SDH volumes were measured from time of initial discovery on imaging to pre-operative, post-operative, short-term and long-term follow-up. Time between procedure to obliteration was also measured. Volumetric analysis was done using the coniglobus formula, and recurrence rate as well as resolution timeline was defined using best-fit models. Results: Out of 10 patients, five were recurrent lesions, three were bilateral and seven unilateral cSDH. Average and median pre-operative volumes were 105.3 cc and 97.4 cc, respectively. Embolization on average was performed 21 days after discovery. Sixty percent of patients had concurrent antiplatelets or anticoagulation use. Forty percent underwent embolization treatment as the primary therapy. Recurrence was not seen in any patients treated with embolization. There were no peri- or post-operative complications. Five patients experienced complete or near-complete obliteration, while those with partial resolution showed a composite average of 75% volumetric reduction in 45 days. Post-embolization, the volumetric resolution followed an exponential decay curve over time and was independent of initial volume. Conclusion: MMA embolization contributed to a marked reduction in SDH volume post-operatively and can be used as a curative therapy for primary or recurrent chronic SDH.

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A Systems Approach to Brain Tumor Treatment

Cancers ◽

10.3390/cancers13133152 ◽

2021 ◽

Vol 13 (13) ◽

pp. 3152

Author(s):

James H. Park ◽

Adrian Lopez Garcia de Lomana ◽

Diego M. Marzese ◽

Tiffany Juarez ◽

Abdullah Feroze ◽

...

Keyword(s):

Brain Tumor ◽

Brain Tumors ◽

Rational Design ◽

Clinical Medicine ◽

Systems Approach ◽

Therapy Resistance ◽

High Rate ◽

Intratumor Heterogeneity ◽

Primary Therapy ◽

Molecular Features

Brain tumors are among the most lethal tumors. Glioblastoma, the most frequent primary brain tumor in adults, has a median survival time of approximately 15 months after diagnosis or a five-year survival rate of 10%; the recurrence rate is nearly 90%. Unfortunately, this prognosis has not improved for several decades. The lack of progress in the treatment of brain tumors has been attributed to their high rate of primary therapy resistance. Challenges such as pronounced inter-patient variability, intratumoral heterogeneity, and drug delivery across the blood–brain barrier hinder progress. A comprehensive, multiscale understanding of the disease, from the molecular to the whole tumor level, is needed to address the intratumor heterogeneity resulting from the coexistence of a diversity of neoplastic and non-neoplastic cell types in the tumor tissue. By contrast, inter-patient variability must be addressed by subtyping brain tumors to stratify patients and identify the best-matched drug(s) and therapies for a particular patient or cohort of patients. Accomplishing these diverse tasks will require a new framework, one involving a systems perspective in assessing the immense complexity of brain tumors. This would in turn entail a shift in how clinical medicine interfaces with the rapidly advancing high-throughput (HTP) technologies that have enabled the omics-scale profiling of molecular features of brain tumors from the single-cell to the tissue level. However, several gaps must be closed before such a framework can fulfill the promise of precision and personalized medicine for brain tumors. Ultimately, the goal is to integrate seamlessly multiscale systems analyses of patient tumors and clinical medicine. Accomplishing this goal would facilitate the rational design of therapeutic strategies matched to the characteristics of patients and their tumors. Here, we discuss some of the technologies, methodologies, and computational tools that will facilitate the realization of this vision to practice.

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Patient disease knowledge, attitudes and behaviours related to non-alcoholic fatty liver disease: a qualitative study

BMJ Open Gastroenterology ◽

10.1136/bmjgast-2021-000634 ◽

2021 ◽

Vol 8 (1) ◽

pp. e000634

Author(s):

Monica A Tincopa ◽

Jane Wong ◽

Michael Fetters ◽

Anna S Lok

Keyword(s):

Social Support ◽

Weight Loss ◽

Liver Disease ◽

Fatty Liver ◽

Health Behaviour ◽

Fatty Liver Disease ◽

Primary Therapy ◽

Alcoholic Fatty Liver ◽

Medical Comorbidities ◽

Alcoholic Fatty Liver Disease

ObjectiveDespite clear evidence that weight loss via nutritional and physical activity changes improves histological outcomes in non-alcoholic fatty liver disease (NAFLD), many patients struggle to implement and maintain these health behaviour changes. The aim of this study was to characterise disease knowledge, attitudes and behaviours among persons with NAFLD and to identify the factors driving these health behaviours and perceptions.DesignWe conducted semistructured interviews among patients with NAFLD. We used purposeful sampling to enroll equivalent percentages based on age and sex, and enrolled approximately one-third of patients with cirrhosis to capture those perspectives. Interviews were conducted until thematic saturation was achieved. Transcripts were coded using NVivo software to identify themes and subthemes.ResultsA total of 29 patient interviews were completed. Ambiguity about the diagnosis and aetiology of their liver disease was a key theme, though the vast majority of patients were aware that weight loss via nutrition and exercise was the primary therapy. Most patients were asymptomatic, diagnosed incidentally, and reported low level of concern regarding their diagnosis. The primary barriers and facilitators to health behaviour change were the presence of social support, competing medical comorbidities and low motivation to change behaviours.ConclusionsAlthough patients are aware that lifestyle interventions are the primary therapy for NAFLD, there is a gap in knowledge about the condition. The presence of social support and competing medical comorbidities were the most consistent facilitators and barriers to lifestyle change. Tailoring treatment recommendations to provide relevant disease education, specific nutrition and exercise regimens, and personalised approaches based on specific individual barriers and facilitators will likely aid in uptake and maintenance of first-line therapy for NAFLD.

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PROTEOMIC BIOMARKER IDENTIFICATION FOR DIAGNOSIS OF EARLY RELAPSE IN OVARIAN CANCER

Journal of Bioinformatics and Computational Biology ◽

10.1142/s0219720006002399 ◽

2006 ◽

Vol 04 (06) ◽

pp. 1159-1179 ◽

Cited By ~ 14

Author(s):

JUNG HUN OH ◽

ANIMESH NANDI ◽

PREM GURNANI ◽

LYNNE KNOWLES ◽

JOHN SCHORGE ◽

...

Keyword(s):

Ovarian Cancer ◽

Feature Selection ◽

Minimum Weight ◽

Early Recurrence ◽

Recursive Feature Elimination ◽

Support Vector ◽

Primary Therapy ◽

Serum Samples ◽

Markov Blanket ◽

Early Relapse

Ovarian cancer recurs at the rate of 75% within a few months or several years later after therapy. Early recurrence, though responding better to treatment, is difficult to detect. Surface-enhanced laser desorption/ionization time-of-flight (SELDI-TOF) mass spectrometry has showed the potential to accurately identify disease biomarkers to help early diagnosis. A major challenge in the interpretation of SELDI-TOF data is the high dimensionality of the feature space. To tackle this problem, we have developed a multi-step data processing method composed of t-test, binning and backward feature selection. A new algorithm, support vector machine-Markov blanket/recursive feature elimination (SVM-MB/RFE) is presented for the backward feature selection. This method is an integration of minimum weight feature elimination by SVM-RFE and information theory based redundant/irrelevant feature removal by Markov Blanket. Subsequently, SVM was used for classification. We conducted the biomarker selection algorithm on 113 serum samples to identify early relapse from ovarian cancer patients after primary therapy. To validate the performance of the proposed algorithm, experiments were carried out in comparison with several other feature selection and classification algorithms.

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APLN: A potential novel biomarker for cervical cancer

Science Progress ◽

10.1177/00368504211011341 ◽

2021 ◽

Vol 104 (2) ◽

pp. 003685042110113

Author(s):

Yusha Chen ◽

Xiaoqian Lin ◽

Jinwen Zheng ◽

Jiancui Chen ◽

Huifeng Xue ◽

...

Keyword(s):

Cervical Cancer ◽

Cox Regression ◽

Clinical Stage ◽

Mapk Signaling ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

High Expression ◽

Receptor Interaction ◽

Primary Therapy ◽

Advanced Clinical Stage

Apelin (APLN) is recently demonstrated a direct association with many malignant diseases. However, its effects on cervical cancer remain unclear. This study therefore aims to evaluate the association between APLN expression and cervical cancer using publicly available data from The Cancer Genome Atlas (TCGA). The Pearson χ2 test and Fish exact test, as well as logistic regression, were used to evaluate the relationship between clinicopathological factors in cervical cancer and the expression of APLN. Additionally, the Cox regression and Kaplan-Meier methods were conducted to analyze the Overall Survival (OS) of cervical cancer patients in TCGA. Finally, gene set enrichment analysis (GSEA) was performed to establish its biological functions. High expression of APLN in cervical cancer was significantly associated with a more advanced clinical stage (OR = 1.91 (1.21–3.05) for Stage II, Stage III, and Stage IV vs Stage I, p = 0.006). Additionally, it was associated with poor outcome after primary therapy (OR = 2.14 (1.03–4.59) for Progressive Disease (PD), Stable Disease (SD), and Partial Response (PR) vs Complete Remission (CR), p = 0.045) and high histologic grade (OR = 1.67 (1.03–2.72) for G3 and G4 vs G1 and G2, p = 0.037). Moreover, multivariate analysis showed that high expression of APLN was associated with a shorter OS. GSEA demonstrated that six KEGG pathways, including PPAR signaling, ECM-receptor interaction, focal adhesion, MAPK signaling, TGF-beta signaling, and Gap junction pathways were differentially enriched in the high expression APLN phenotype. The recent study suggests that APLN plays an important role in the progression of cervical cancer and might be a promising prognostic biomarker of the disease.

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