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Rheumatology (Oxford, England) Mar 2021
Topics: Disease Progression; Female; Humans; Male; Middle Aged; Scleroderma, Systemic; Time Factors
PubMed: 33404661
DOI: 10.1093/rheumatology/keaa911 -
Annals of Palliative Medicine Jan 2022Lung cancer has the highest incidence rate and mortality rate of all malignancies. In recent years, the therapeutic effect of lung cancer has been greatly improved, but...
BACKGROUND
Lung cancer has the highest incidence rate and mortality rate of all malignancies. In recent years, the therapeutic effect of lung cancer has been greatly improved, but the fear of disease progression still directly affects the quality of life (QOL) of patients. The aim of this study was to evaluate the factors affecting the progression of fear of disease and its impact on the quality of life in patients with lung cancer.
METHODS
From December 2019 to February 2020, 102 patients with lung cancer in the Department of Thoracic Oncology of a top three hospital were investigated by using the simplified fear of disease progression scale (FoP-Q-SF) and the quality-of-life scale for cancer patients (FACT-G). Data were collected and statistically analyzed by SPSS25.0 software.
RESULTS
A total of 110 questionnaires were distributed and 102 valid questionnaires were recovered, indicating a recovery rate of 92.7%. The results of multiple stepwise regression analyses showed that blood group, monthly income, and mood state were the influencing factors for the progression of phobic diseases in cancer patients (P<0.05), and the score of progression of phobic disease was negatively correlated with the quality-of-life score (r=-0.382).
CONCLUSIONS
The progress of phobic diseases in patients with lung cancer seriously affects their QOL, and further attention by medical staff in providing health education, psychological counseling, social support, and other measures is required.
Topics: Disease Progression; Fear; Humans; Lung Neoplasms; Quality of Life; Surveys and Questionnaires
PubMed: 35144396
DOI: 10.21037/apm-21-2821 -
Statistics in Medicine Aug 2023Disease modeling is an essential tool to describe disease progression and its heterogeneity across patients. Usual approaches use continuous data such as biomarkers to...
Disease modeling is an essential tool to describe disease progression and its heterogeneity across patients. Usual approaches use continuous data such as biomarkers to assess progression. Nevertheless, categorical or ordinal data such as item responses in questionnaires also provide insightful information about disease progression. In this work, we propose a disease progression model for ordinal and categorical data. We built it on the principles of disease course mapping, a technique that uniquely describes the variability in both the dynamics of progression and disease heterogeneity from multivariate longitudinal data. This extension can also be seen as an attempt to bridge the gap between longitudinal multivariate models and the field of item response theory. Application to the Parkinson's progression markers initiative cohort illustrates the benefits of our approach: a fine-grained description of disease progression at the item level, as compared to the aggregated total score, together with improved predictions of the patient's future visits. The analysis of the heterogeneity across individual trajectories highlights known disease trends such as tremor dominant or postural instability and gait difficulties subtypes of Parkinson's disease.
Topics: Humans; Disease Progression; Tremor; Parkinson Disease; Biomarkers
PubMed: 37231622
DOI: 10.1002/sim.9770 -
Clinical & Experimental Ophthalmology 2023Current glaucoma management centres on intraocular pressure (IOP) reduction through pharmacological and surgical therapy. Despite broad interest in active management of... (Review)
Review
Current glaucoma management centres on intraocular pressure (IOP) reduction through pharmacological and surgical therapy. Despite broad interest in active management of glaucoma through lifestyle modifications, such recommendations have yet to be incorporated into standards of treatment. In this review, noteworthy preclinical studies and their translations in clinical populations are discussed to evaluate the roles of lifestyle factors in lowering IOP, offering neuroprotection, and/or slowing disease progression in those with open-angle glaucoma. Current literature suggests that aerobic exercise may be associated with neuroprotection and decreased disease progression. Mindfulness is associated with IOP reductions and neuroprotection. Caffeine is associated with mild, transient IOP elevations of uncertain significance. Nicotinamide supplementation is associated with neuroprotection and short-term visual function improvement. This review also highlights knowledge gaps regarding these factors and opportunities to strengthen our understanding of their role in glaucoma, including future preclinical studies that elucidate underlying mechanisms and clinical studies with additional functional endpoints and longer follow-up.
Topics: Humans; Intraocular Pressure; Glaucoma, Open-Angle; Neuroprotection; Glaucoma; Disease Progression; Ocular Hypotension; Life Style
PubMed: 36859798
DOI: 10.1111/ceo.14218 -
Nutrition and Health Mar 2023It has been suggested that the lowering of dietary protein reduces the progression of CKD, despite it has been also reported that higher intake of total protein was...
It has been suggested that the lowering of dietary protein reduces the progression of CKD, despite it has been also reported that higher intake of total protein was associated with a lower risk of cardiovascular morbidity.The role of protein intake is equivocal in clinical outcomes including the renal and cardiovascular disease worsening, metabolic acidosis and bone abnormalities.The modification of both amount and sources of protein intake could influence the renal and cardiovascular deterioration.
Topics: Humans; Renal Insufficiency, Chronic; Disease Progression; Cardiovascular Diseases
PubMed: 35946110
DOI: 10.1177/02601060221118897 -
Cancer Letters Nov 2022
Topics: Disease Progression; Humans; Neoplasms; Tumor Microenvironment
PubMed: 36031152
DOI: 10.1016/j.canlet.2022.215888 -
Journal of B.U.ON. : Official Journal... 2019Immune checkpoint inhibitors have revolutionized cancer treatment with patient improved survival, quality of life, and a longer response. However, up to 30% of patients... (Review)
Review
Immune checkpoint inhibitors have revolutionized cancer treatment with patient improved survival, quality of life, and a longer response. However, up to 30% of patients experience paradoxical accelerated tumor progression early after immune-checkpoint blockade therapy. This phenomenon is also known as hyperprogression (HP). Unlike other responses, such as pseudoprogression or natural progression, HP causes worse survival outcomes in patients. Older age, higher metastatic burden, and previous radiation have been independently associated with HP. Even though the exact molecular mechanism underlying HP after immune-checkpoint blockade therapy remains unknown, oncogenic signaling activation including MDM2 amplification or EGFR alterations, the modification of tumor microenvironment by radiotherapy with immune checkpoint inhibitors, and alterations in immune landscape of tumors have been hypothesized as the biological mechanisms behind HP. Patients with HP have been presented with poor prognosis and increased deleterious mutations in cancer genes, along with alterations in the tumor microenvironment. As immune checkpoint inhibitors have been more widely accepted by oncologists, proper assessment of this unique tumor response remains challenging in clinical practice. This work documents the recent findings on epidemiology, biological and clinicopathological factors of HP after immunotherapy.
Topics: Disease Progression; Humans; Immunotherapy
PubMed: 31983088
DOI: No ID Found -
Revue Medicale Suisse Apr 2022
Topics: Disease Progression; Humans; Pulmonary Disease, Chronic Obstructive
PubMed: 35481529
DOI: 10.53738/REVMED.2022.18.779.861 -
Nature Reviews. Neuroscience Feb 2024Data-driven disease progression models are an emerging set of computational tools that reconstruct disease timelines for long-term chronic diseases, providing unique... (Review)
Review
Data-driven disease progression models are an emerging set of computational tools that reconstruct disease timelines for long-term chronic diseases, providing unique insights into disease processes and their underlying mechanisms. Such methods combine a priori human knowledge and assumptions with large-scale data processing and parameter estimation to infer long-term disease trajectories from short-term data. In contrast to 'black box' machine learning tools, data-driven disease progression models typically require fewer data and are inherently interpretable, thereby aiding disease understanding in addition to enabling classification, prediction and stratification. In this Review, we place the current landscape of data-driven disease progression models in a general framework and discuss their enhanced utility for constructing a disease timeline compared with wider machine learning tools that construct static disease profiles. We review the insights they have enabled across multiple neurodegenerative diseases, notably Alzheimer disease, for applications such as determining temporal trajectories of disease biomarkers, testing hypotheses about disease mechanisms and uncovering disease subtypes. We outline key areas for technological development and translation to a broader range of neuroscience and non-neuroscience applications. Finally, we discuss potential pathways and barriers to integrating disease progression models into clinical practice and trial settings.
Topics: Humans; Neurodegenerative Diseases; Alzheimer Disease; Disease Progression
PubMed: 38191721
DOI: 10.1038/s41583-023-00779-6 -
Headache Jul 2020
Topics: Disease Progression; Humans; Migraine Disorders
PubMed: 32510587
DOI: 10.1111/head.13837