Objectives Multiple studies have proven the prognostic value of molecular classification for stage I–III endometrial cancer patients. However, studies on the relevance of molecular classification... Show moreObjectives Multiple studies have proven the prognostic value of molecular classification for stage I–III endometrial cancer patients. However, studies on the relevance of molecular classification for stage IV endometrial cancer patients are lacking. Hypothetically, poor prognostic molecular subtypes are more common in higher stages of endometrial cancer. Considering the poor prognosis of stage IV endometrial cancer patients, it is questionable whether molecular classification has additional prognostic value. Therefore, we determined which molecular subclasses are found in stage IV endometrial cancer and if there is a correlation with progression-free and overall survival.Methods A retrospective multicenter cohort study was conducted using data from five Dutch hospitals. Patients with stage IV endometrial cancer at diagnosis who were treated with primary cytoreductive surgery or cytoreductive surgery after induction chemotherapy between January 2000 and December 2018 were included. Exclusion criteria were age <18 years or recurrent disease. The molecular classification was performed centrally on all tumor samples according to the World Health Organization 2020 classification (including POLE and estrogen receptor status). The Kaplan–Meier method was used to calculate progression free and overall survival in the molecular subclasses, for the different histological subtypes and for estrogen receptor positive versus estrogen receptor negative tumors. Groups were compared using the log-rank test.Results 164 stage IV endometrial cancer patients were molecularly classified. Median age of the patients was 67 years (range 33–86). Most patients presented with a non-endometrioid histological subtype (58%). Intra-abdominal complete cytoreductive surgery was achieved in 60.4% of the patients. 101 tumors (61.6%) were classified as p53 abnormal, 35 (21.3%) as no specific molecular profile, 21 (12.8%) as mismatch repair deficient, and 6 (3%) as POLE mutated. Molecular classification had no significant impact on progression free (p=0.056) or overall survival (p=0.12) after cytoreductive surgery. Overall survival was affected by histologic subtype (p<0.0001) and estrogen receptor status (p=0.013).Conclusion The distribution of the molecular subclasses in stage IV endometrial cancer patients differed substantially from the distribution in stage I–III endometrial cancer patients, with the unfavorable subclasses being more frequently present. Although the molecular classification was not prognostic in stage IV endometrial cancer, it could guide adjuvant treatment decisions. Show less
Fluency, comprehensibility, and accentedness are considered importantparameters of interpreting quality but have rarely been studiedsystematically in training programs of interpreting. Therefore,... Show moreFluency, comprehensibility, and accentedness are considered importantparameters of interpreting quality but have rarely been studiedsystematically in training programs of interpreting. Therefore, the presentstudy was set up to investigate the effect of fluency training on speechfluency, comprehensibility, and accentedness of interpreter trainees. Twogroups of interpreter trainees at a university in Iran took part in the study,receiving the same amount of instruction and practice (12 hours over 4weeks). The experimental group (N=30) spent 33% of the time (i.e., 4 of the12 hours in the training program) on dedicated fluency strategy training,encouraging the memorization, repetition, and retelling of audio and videomaterials. The remaining 67% was spent on training general speaking skills.The control group (N=30) were only taught general speaking skills in thetraining program but received no dedicated fluency training. Systematicinterviews were run to assess the interpreter trainees’ speech fluency,comprehensibility and accentedness, which were judged independently bythree expert raters at three moments of testing, i.e., pretest, immediateposttest, and delayed posttest (one month later). The findings revealed thatthe fluency training significantly enhanced the interpreter trainees’ fluency,and to a lesser extent the students’ comprehensibility but had only amarginal effect on accentedness. The pedagogical implication would be thatawareness training on speech fluency Show less
The current research examines joint collective action between advantaged and disadvantaged groups, from the perspective of the latter. We hypothesize that joint action poses a dilemma which lies in... Show moreThe current research examines joint collective action between advantaged and disadvantaged groups, from the perspective of the latter. We hypothesize that joint action poses a dilemma which lies in the tension between perceived instrumentality of joint action (i.e., ability to promote the disadvantaged’s goals) and perceived normalization (i.e., its tendency to blur power relations). We test this idea across three studies in the United States and Israel/Palestine. In Study 1 (n = 361) we manipulated perceptions of joint action from the perspective of a hypothetical character, and in Study 2 (n = 378) we presented participants with an article highlighting the risk and benefit of joint activism. Results showed that perceived instrumentality increases, whereas perceived normalization decreases joint action tendencies. In Study 3 (n = 240), we described a joint action event that taps into some of the themes that induce concerns about normalization. We found that normalization perceptions feed into perceptions of instrumentality, and this occurred mainly among high identifiers, for whom the dilemma is most salient. The implications of these findings for understanding the complexity of joint collective action from the perspective of the disadvantaged are discussed. Show less
Importance Multiple patient-reported outcome measures (PROMs) for health-related quality of life (HRQL) exist for patients with psoriasis. Evidence for the content validity and other measurement... Show moreImportance Multiple patient-reported outcome measures (PROMs) for health-related quality of life (HRQL) exist for patients with psoriasis. Evidence for the content validity and other measurement properties of these PROMs is critical to determine which HRQL PROMs could be recommended for use.Objective To systematically review the validity of HRQL-focused PROMs used in patients with psoriasis.Evidence Review Using PubMed and Embase, full-text articles published in English or Spanish on development or validation studies for psoriasis-specific, dermatology-specific, or generic HRQL PROMs were included. Development studies included original development studies, even if not studied in psoriasis patients per Consensus-Based Standards for the Selection of Health Measurement Instruments (COSMIN) recommendations. If a study included multiple diagnoses, more than 50% of patients had to have psoriasis or psoriasis-specific subgroup analyses available. Data extraction and analysis followed the COSMIN guidelines. Two independent reviewers extracted and analyzed the data, including PROM characteristics, quality of measurement properties (structural validity, internal consistency, cross-cultural validity, reliability, measurement error, criterion validity, construct validity, and responsiveness), and level of evidence. PROMs were classified into 3 levels of recommendations: (1) PROM recommended for use; (2) PROM requires further validation; and (3) PROM not recommended for use.Findings Overall, 97 articles were identified for extraction. This included 19 psoriasis-specific, 8 skin-specific, and 6 generic PROMs. According to COSMIN standards, most measures identified received a B recommendation for use, indicating their potential but requiring further validation. Only the Rasch reduced version of the Impact of Psoriasis Questionnaire (IPSO-11 Rasch) received an A recommendation for use given that it had sufficient content validity, structural validity, and internal consistency.Conclusions and Relevance This study identified a significant lack of information concerning the quality of HRQL measures in psoriasis. This gap in knowledge can be attributed to the fact that traditional measures were developed using validation criteria that differ from the current standards in use. Consequently, additional validation studies in accordance with contemporary standards will be useful in aiding researchers and clinicians in determining the most suitable measure for assessing HRQL in patients with psoriasis. Show less
In theory, it can be strategically advantageous for competitors to make themselves unpredictable to their opponents, for example, by variably mixing hostility and friendliness. Empirically, it... Show moreIn theory, it can be strategically advantageous for competitors to make themselves unpredictable to their opponents, for example, by variably mixing hostility and friendliness. Empirically, it remains open whether and how competitors make themselves unpredictable, why they do so, and how this conditions conflict dynamics and outcomes. We examine these questions in interactive attacker–defender contests, in which attackers invest to capture resources held and defended by their opponent. Study 1, a reanalysis of nine (un)published experiments (total N = 650), reveals significant cross-trial variability especially in proactive attacks and less in reactive defense. Study 2 (N = 200) shows that greater variability makes both attacker’s and defender’s next move more difficult to predict, especially when variability is due to occasional rather than (in)frequent extreme investments in conflict. Studies 3 (N = 27) and 4 (N = 106) show that precontest testosterone, a hormone associated with risk-taking and status competition, drives variability during attack which, in turn, increases sympathetic arousal in defenders and defender variability (Study 4). Rather than being motivated by wealth maximization, being unpredictable in conflict and competition emerges in function of the attacker’s desire to win “no matter what” and comes with significant welfare cost to both victor and victim. Show less
The search for biomarkers that quantify biological aging (particularly 'omic'-based biomarkers) has intensified in recent years. Such biomarkers could predict aging-related outcomes and could serve... Show moreThe search for biomarkers that quantify biological aging (particularly 'omic'-based biomarkers) has intensified in recent years. Such biomarkers could predict aging-related outcomes and could serve as surrogate endpoints for the evaluation of interventions promoting healthy aging and longevity. However, no consensus exists on how biomarkers of aging should be validated before their translation to the clinic. Here, we review current efforts to evaluate the predictive validity of omic biomarkers of aging in population studies, discuss challenges in comparability and generalizability and provide recommendations to facilitate future validation of biomarkers of aging. Finally, we discuss how systematic validation can accelerate clinical translation of biomarkers of aging and their use in gerotherapeutic clinical trials.Robust validation of biomarkers of aging will be critical to their clinical translation; here, authors review the key challenges and propose recommendations to overcome them. Show less
This Viewpoint discusses the potential drawbacks of the use of artificial intelligence (AI) in medicine, for example, the loss of certain skills due to the reliance on AI, and how physicians should... Show moreThis Viewpoint discusses the potential drawbacks of the use of artificial intelligence (AI) in medicine, for example, the loss of certain skills due to the reliance on AI, and how physicians should consider how to take advantage of the potential benefits of AI without losing control over their profession. Show less
Rosendal, C.; Arlien-Soborg, M.C.; Nielsen, E.H.; Andersen, M.S.; Feltoft, C.L.; Kistorp, C.; ... ; J. dal 2024
Acromegaly is a rare disease and thus challenging to accurately quantify epidemiologically. In this comprehensive literature review, we compare different approaches to studying acromegaly from an... Show moreAcromegaly is a rare disease and thus challenging to accurately quantify epidemiologically. In this comprehensive literature review, we compare different approaches to studying acromegaly from an epidemiological perspective and describe the temporal evolution of the disease pertaining to epidemiological variables, clinical presentation and mortality. We present updated epidemiological data from the population-based Danish cohort of patients with acromegaly (AcroDEN), along with meta-analyses of existing estimates from around the world.Based on this, we conclude that the incidence, prevalence and age at acromegaly diagnosis are all steadily increasing, but with considerable variation between studies. An increased number of incidental cases may contribute to the increase in incidence and age at diagnosis, respectively. The clinical features at presentation are trending toward a milder disease phenotype at diagnosis, and advances in therapeutic options have reduced the mortality of patients with acromegaly to a level similar to that of the general population. Moreover, the underlying cause of death has shifted from cardiovascular to malignant neoplastic diseases. Show less
Stoel, B.C.; Staring, M.; Reijnierse, M.; Helm-van Mil, A.H.M. van der 2024
Artificial intelligence techniques, specifically deep learning, have already affected daily life in a wide range of areas. Likewise, initial applications have been explored in rheumatology. Deep... Show moreArtificial intelligence techniques, specifically deep learning, have already affected daily life in a wide range of areas. Likewise, initial applications have been explored in rheumatology. Deep learning might not easily surpass the accuracy of classic techniques when performing classification or regression on low-dimensional numerical data. With images as input, however, deep learning has become so successful that it has already outperformed the majority of conventional image-processing techniques developed during the past 50 years. As with any new imaging technology, rheumatologists and radiologists need to consider adapting their arsenal of diagnostic, prognostic and monitoring tools, and even their clinical role and collaborations. This adaptation requires a basic understanding of the technical background of deep learning, to efficiently utilize its benefits but also to recognize its drawbacks and pitfalls, as blindly relying on deep learning might be at odds with its capabilities. To facilitate such an understanding, it is necessary to provide an overview of deep-learning techniques for automatic image analysis in detecting, quantifying, predicting and monitoring rheumatic diseases, and of currently published deep-learning applications in radiological imaging for rheumatology, with critical assessment of possible limitations, errors and confounders, and conceivable consequences for rheumatologists and radiologists in clinical practice.Deep learning is a powerful technique with great potential for the analysis and interpretation of rheumatological images. To successfully use deep learning, rheumatologists should understand the tasks involved in image processing and the potential confounders and limitations that can affect the analysis of clinical data.The number of research studies on deep learning in rheumatological imaging has grown rapidly during the past 5 years, but they mainly consist of pilot studies that require external validation.Confounding factors and errors in deep-learning methods need to be ruled out before deep learning can be applied in clinical practice, for which the intended use should be strictly defined.Deep-learning techniques, together with mapping to explain their reasoning, will enable hypothesis-free image analysis and could identify new imaging biomarkers.Deep learning might assist rheumatologists and radiologists in interpreting rheumatological images, increasing their diagnostic, prognostic and monitoring accuracy, and decreasing workloads and costs. Show less
Schenning, L.C.M.; Ottevanger, R.; Quint, K.D.; Tas, S.W. 2024
Rheumatoid Arthritis (RA) is an autoimmune disease that mainly affects joints in the wrist and hands. It typically results in inflamed and painful joints. MRI is one of the most common imaging...Show moreRheumatoid Arthritis (RA) is an autoimmune disease that mainly affects joints in the wrist and hands. It typically results in inflamed and painful joints. MRI is one of the most common imaging modalities to detect and monitor possible inflamed RA-related areas, enabling rheumatologists to treat patients more timely and efficiently. Despite the importance of finding and tracking inflamed areas associated with RA in MRI, there is no previously published work on finding pixel-by-pixel changes related to RA between baseline and follow-up MRIs. Therefore, this paper proposes a hypothesis-free deep learning-based model to discover changes in wrist MRIs on a pixel level to detect changes in inflamed areas related to RA without using prior anatomical information. To do this, a combination of a U-Net-based network and image thresholding was utilised to find pixel-level non-trivial changes between baseline and follow-up MRI images. A wrist MRI dataset including 99 individual pairs of MRI images (each pair constructed of baseline and follow-up images) was used to evaluate the proposed model. Data were collected from patients with clinically suspected arthralgia (CSA), defined as patients at risk of developing RA according to their rheumatologist and already had subclinical inflammation on MRI but could not be diagnosed with RA (yet) since they had not developed clinically detectable arthritis. The obtained results were evaluated using an observer study. The evaluation showed that our proposed model is a promising first step toward developing an automatic model to find RA-related inflammatory changes. Show less
