| 1. |
- Houben-Wilke, Sarah, et al.
(author)
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Revealing Methodological Challenges in Chronic Obstructive Pulmonary Disease Studies Assessing Comorbidities: A Narrative Review.
- 2019
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In: Chronic obstructive pulmonary diseases (Miami, Fla.). - : COPD Foundation. - 2372-952X. ; 6:2, s. 166-77
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Journal article (peer-reviewed)abstract
- Beyond respiratory impairment, patients with chronic obstructive pulmonary disease (COPD) often suffer from comorbidities which are associated with worse health status, higher health care costs and worse prognosis. Reported prevalences of comorbidities largely differ between studies which might be explained by different assessment methods (objective assessment, self-reported assessment, or assessment by medical records), heterogeneous study populations, inappropriate control groups, incomparable methodologies, etc. This narrative review demonstrates and further evaluates the variability in prevalence of several comorbidities in patients with COPD and control individuals and discusses several shortcomings and pitfalls which need to be considered when interpreting comorbidity data. Like in other chronic organ diseases, the accurate diagnosis and integrated management of comorbidities is a key for outcome in COPD. This review highlights that there is a need to move from the starting point of an established index disease towards the concept of the development of multimorbidity in the elderly including COPD as an important and highly prevalent pulmonary component.
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| 2. |
- Jonsdottir, Kristin, et al.
(author)
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The prognostic value of MARCKS-like 1 in lymph node-negative breast cancer
- 2012
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In: Breast Cancer Research and Treatment. - : Springer. - 0167-6806 .- 1573-7217. ; 135:2, s. 381-390
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Journal article (peer-reviewed)abstract
- There is a need for new biomarkers to more correctly identify node-negative breast cancer patients with a good or bad prognosis. Myristoylated alanine-rich C kinase substrate like-1 (MARCKSL1) is a membrane-bound protein that is associated with cell spreading, integrin activation and exocytosis. Three hundred and five operable T1,2N0M0 lymph node-negative breast cancer patients (median follow-up time 121 months, range 10–178 months) were evaluated for MARCKSL1 expression by immunohistochemistry and quantitative real-time PCR. The results were compared with classical prognosticators (age, tumor diameter, grade, estrogen receptor, and proliferation), using single (Kaplan–Meier) and multivariate survival analysis (Cox model). Forty-seven patients (15 %) developed distant metastases. With single and multivariate analysis of all features, MARCKSL1 protein expression was the strongest prognosticator (P < 0.001, HR = 5.1, 95 % CI = 2.7–9.8). Patients with high MARCKSL1 expression (n = 23) showed a 44 % survival versus 88 % in patients with low expression at 15-year follow-up. mRNA expression of MARCKSL1 in formalin fixed paraffin-embedded tissue was also prognostic (P = 0.002, HR = 3.6, 95 % CI = 1.5–8.3). However, the prognostic effect of high and low was opposite from the protein expression, i.e., low expression (relative expression ≤ 0.0264, n = 76) showed a 79 % survival versus 92 % in those with high expression of MARCKSL1 mRNA. Multivariate analysis of all features with distant metastases free survival as the end-point showed that the combination of MARCKSL1 protein and phosphohistone H3 (PPH3) has the strongest independent prognostic value. Patients with high expression (≥13) of PPH3 and high MARCKSL1 protein had 45 % survival versus 78 % survival for patients with low MARCKSL1 protein expression and high expression (≥13) of PPH3. In conclusion, MARCKSL1 has strong prognostic value in lymph node-negative breast cancer patients, especially in those with high proliferation.
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| 3. |
- Klintman, Marie, et al.
(author)
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The Prognostic Value of Mitotic Activity Index (MAI), Phosphohistone H3 (PPH3), Cyclin B1, Cyclin A, and Ki67, Alone and in Combinations, in Node-Negative Premenopausal Breast Cancer
- 2013
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In: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 8:12
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Journal article (peer-reviewed)abstract
- Proliferation, either as the main common denominator in genetic profiles, or in the form of single factors such as Ki67, is recommended for clinical use especially in estrogen receptor-positive (ER) patients. However, due to high costs of genetic profiles and lack of reproducibility for Ki67, studies on other proliferation factors are warranted. The aim of the present study was to evaluate the prognostic value of the proliferation factors mitotic activity index (MAI), phosphohistone H3 (PPH3), cyclin B1, cyclin A and Ki67, alone and in combinations. In 222 consecutive premenopausal node-negative breast cancer patients (87% without adjuvant medical treatment), MAI was assessed on whole tissue sections (predefined cut-off >= 10 mitoses), and PPH3, cyclin B1, cyclin A, and Ki67 on tissue microarray (predefined cut-offs 7th decile). In univariable analysis (high versus low) the strongest prognostic proliferation factor for 10-year distant disease-free survival was MAI (Hazard Ratio (HR)=3.3, 95% Confidence Interval (CI): 1.8-6.1), followed by PPH3, cyclin A, Ki67, and cyclin B1. A combination variable, with patients with MAI and/or cyclin A high defined as high-risk, had even stronger prognostic value (HR=4.2, 95% CI: 2.2-7). When stratifying for ER-status, MAI was a significant prognostic factor in ER-positive patients only (HR=7.0, 95% CI: 3.1-16). Stratified for histological grade, MAI added prognostic value in grade 2 (HR=7.2, 95% CI: 3.1-38) and grade 1 patients. In multivariable analysis including HER2, age, adjuvant medical treatment, ER, and one proliferation factor at a time, only MAI (HR=2.7, 95% CI: 1.1-6.7), and cyclin A (HR=2.7, 95% CI: 1.2-6.0) remained independently prognostic. In conclusion this study confirms the strong prognostic value of all proliferation factors, especially MAI and cyclin A, in all patients, and more specifically in ER-positive patients, and patients with histological grade 2 and 1. Additionally, by combining two proliferation factors, an even stronger prognostic value may be found.
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| 4. |
- Norheim, Katrine Braekke, et al.
(author)
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Epigenome-wide DNA methylation patterns associated with fatigue in primary Sjogren's syndrome
- 2016
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In: Rheumatology. - : Oxford University Press (OUP). - 1462-0324 .- 1462-0332. ; 55:6, s. 1074-1082
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Journal article (peer-reviewed)abstract
- Objective. Chronic fatigue is a common, disabling and poorly understood phenomenon. Recent studies indicate that epigenetic mechanisms may be involved in the expression of fatigue, a prominent feature of primary SS (pSS). The aim of this study was to investigate whether DNA methylation profiles of whole blood are associated with fatigue in patients with pSS. Methods. Forty-eight pSS patients with high (n = 24) or low (n = 24) fatigue as measured by a visual analogue scale were included. Genome-wide DNA methylation was investigated using the Illumina HumanMethylation450 BeadChip array. After quality control, a total of 383 358 Cytosine-phosphate-Guanine (CpG) sites remained for further analysis. Age, sex and differential cell count estimates were included as covariates in the association model. A false discovery rate-corrected P < 0.05 was considered significant, and a cut-off of 3% average difference in methylation levels between high- and low-fatigue patients was applied. Results. A total of 251 differentially methylated CpG sites were associated with fatigue. The CpG site with the most pronounced hypomethylation in pSS high fatigue annotated to the SBF2-antisense RNA1 gene. The most distinct hypermethylation was observed at a CpG site annotated to the lymphotoxin alpha gene. Functional pathway analysis of genes with differently methylated CpG sites in subjects with high vs low fatigue revealed enrichment in several pathways associated with innate and adaptive immunity. Conclusion. Some genes involved in regulation of the immune system and in inflammation are differently methylated in pSS patients with high vs low fatigue. These findings point to functional networks that may underlie fatigue. Epigenetic changes could constitute a fatigue-regulating mechanism in pSS.
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| 5. |
- Olsson, Henrik, et al.
(author)
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Estimating diagnostic uncertainty in artificial intelligence assisted pathology using conformal prediction
- 2022
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In: Nature Communications. - : Springer Nature. - 2041-1723. ; 13:1
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Journal article (peer-reviewed)abstract
- Unreliable predictions can occur when an artificial intelligence (AI) system is presented with data it has not been exposed to during training. We demonstrate the use of conformal prediction to detect unreliable predictions, using histopathological diagnosis and grading of prostate biopsies as example. We digitized 7788 prostate biopsies from 1192 men in the STHLM3 diagnostic study, used for training, and 3059 biopsies from 676 men used for testing. With conformal prediction, 1 in 794 (0.1%) predictions is incorrect for cancer diagnosis (compared to 14 errors [2%] without conformal prediction) while 175 (22%) of the predictions are flagged as unreliable when the AI-system is presented with new data from the same lab and scanner that it was trained on. Conformal prediction could with small samples (N = 49 for external scanner, N = 10 for external lab and scanner, and N = 12 for external lab, scanner and pathology assessment) detect systematic differences in external data leading to worse predictive performance. The AI-system with conformal prediction commits 3 (2%) errors for cancer detection in cases of atypical prostate tissue compared to 44 (25%) without conformal prediction, while the system flags 143 (80%) unreliable predictions. We conclude that conformal prediction can increase patient safety of AI-systems.
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