Clinical text classification in Cancer Real-World Data in Spanish

Healthcare systems currently store a large amount of clinical data, mostly unstructured textual information, such as electronic health records (EHRs). Manually extracting valuable information from these documents is costly for healthcare professionals. For example, when a patient first arrives at an oncology clinical analysis unit, clinical staff must extract information about the type of neoplasm in order to assign the appropriate clinical specialist. Automating this task is equivalent to text classification in natural language processing (NLP). In this study, we have attempted to extract the neoplasm type by processing Spanish clinical documents. A private corpus of 23, 704 real clinical cases has been processed to extract the three most common types of neoplasms in the Spanish territory: breast, lung and colorectal neoplasms. We have developed methodologies based on state-of-the-art text classification task, strategies based on machine learning and bag-of-words, based on embedding models in a supervised task, and based on bidirectional recurrent neural networks with convolutional layers (C-BiRNN). The results obtained show that the application of NLP methods is extremely helpful in performing the task of neoplasm type extraction. In particular, the 2-BiGRU model with convolutional layer and pre-trained fastText embedding obtained the best performance, with a macro-average, more representative than the micro-average due to the unbalanced data, of 0.981 for precision, 0.984 for recall and 0.982 for F1-score.The authors acknowledge the support from the Ministerio de Ciencia e Innovación (MICINN) under project PID2020-116898RB-I00, from Universidad de Málaga and Junta de Andalucía through grants UMA20-FEDERJA-045 and PYC20-046-UMA (all including FEDER funds), and from the Malaga-Pfizer consortium for AI research in Cancer - MAPIC. Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Explainable clinical coding with in-domain adapted transformers

Background and Objective: Automatic clinical coding is a crucial task in the process of extracting relevant in-formation from unstructured medical documents contained in Electronic Health Records (EHR). However, most of the existing computer-based methods for clinical coding act as “black boxes”, without giving a detailed description of the reasons for the clinical-coding assignments, which greatly limits their applicability to real-world medical scenarios. The objective of this study is to use transformer-based models to effectively tackle explainable clinical-coding. In this way, we require the models to perform the assignments of clinical codes to medical cases, but also to provide the reference in the text that justifies each coding assignment. Methods: We examine the performance of 3 transformer-based architectures on 3 different explainable clinical-coding tasks. For each transformer, we compare the performance of the original general-domain version with an in-domain version of the model adapted to the specificities of the medical domain. We address the explainable clinical-coding problem as a dual medical named entity recognition (MER) and medical named entity normal-ization (MEN) task. For this purpose, we have developed two different approaches, namely a multi-task and a hierarchical-task strategy. Results: For each analyzed transformer, the clinical-domain version significantly outperforms the corresponding general domain model across the 3 explainable clinical-coding tasks analyzed in this study. Furthermore, the hierarchical-task approach yields a significantly superior performance than the multi-task strategy. Specifically, the combination of the hierarchical-task strategy with an ensemble approach leveraging the predictive capa-bilities of the 3 distinct clinical-domain transformersFunding for open access charge: Universidad de Málaga / CBUA. The authors thankfully acknowledge the computer resources, technical expertise and assistance provided by the SCBI (Supercomputing and Bioinformatics) center of the University of Málaga

Detection of tumor morphology mentions in clinical reports in spanish using transformers

The aim of this study is to systematically examine the performance of transformer-based models for the detection of tumor morphology mentions in clinical documents in Spanish. For this purpose, we analyzed 3 transformer models supporting the Spanish language, namely multilingual BERT, BETO and XLM-RoBERTa. By means of a transfer- learning-based approach, the models were first pretrained on a collection of real-world oncology clinical cases with the goal of adapting trans- formers to the distinctive features of the Spanish oncology domain. The resulting models were further fine-tuned on the Cantemist-NER task, addressing the detection of tumor morphology mentions as a multi-class sequence-labeling problem. To evaluate the effectiveness of the proposed approach, we compared the obtained results by the domain-specific ver- sion of the examined transformers with the performance achieved by the general-domain version of the models. The results obtained in this pa- per empirically demonstrated that, for every analyzed transformer, the clinical version outperformed the corresponding general-domain model on the detection of tumor morphology mentions in clinical case reports in Spanish. Additionally, the combination of the transfer-learning-based approach with an ensemble strategy exploiting the predictive capabilities of the distinct transformer architectures yielded the best obtained results, achieving a precision value of 0.893, a recall of 0.887 and an F1-score of 0.89, which remarkably surpassed the prior state-of-the-art performance for the Cantemist-NER task

Validation of the upper limb functional index on breast cancer survivor

Breast cancer survivors (BCS) may face functional alterations after surgical intervention. Upper Limb Disorders (ULDs) are highly prevalent even years after a diagnosis. Clinicians may assess the upper limbs after breast cancer. The Upper Limb Functional Index (ULFI) has been validated across different populations and languages. This study aimed to assess the psychometric properties of the Upper Limb Functional Index Spanish version (ULFI-Sp) in the BCS. Methods: A psychometric validation study of the ULFI-Sp was conducted on 216 voluntary breast cancer survivors. The psychometric properties were as follows: analysis of the factor structure by maximum likelihood extraction (MLE), internal consistency, and construct validity by confirmatory factor analysis (CFA). Results: The factor structure was one-dimensional. ULFI-Sp showed a high internal consistency for the total score (α = 0.916) and the regression score obtained from MLE (α = 0.996). CFA revealed a poor fit, and a new 14-item model (short version) was further tested. The developed short version of the ULFI-SP is preferable to assess upper limb function in Spanish BCS. Conclusions: Given the high prevalence of ULD in this population and the broader versions of ULFI across different languages, this study’s results may be transferred to clinical practice and integrated as part of upper limb assessment after breast cancer.Partial funding for open access charge: Universidad de Málag

Confirmation of preeclampsia-like syndrome induced by severe COVID-19 : An Observational Study

Since the outbreak of the COVID-19 pandemic, some studies have reported an increased preeclampsia (PE) incidence in pregnant women with SARS-CoV-2 infection. Several explanations for this association have been proposed, including a preeclampsia-like syndrome induced by severe COVID-19. This syndrome was described in a small case series and has not been confirmed in larger studies and its impact in perinatal outcomes has not been studied. The aim of this study was to confirm the preeclampsia-like syndrome due to COVID-19 and to investigate its implications in pregnancy outcomes and prognosis. This was a prospective, observational study conducted in a tertiary referral hospital. Inclusion criteria were pregnant women admitted to the Intensive Care Unit for severe pneumonia due to COVID-19. They were classified in three groups based on clinical and laboratory findings: PE, PE-like syndrome, and women without PE features. The three cohorts were analyzed and compared at three different times: before, during and after severe pneumonia. The main outcomes were incidence of adverse perinatal outcomes and signs and symptoms of PE, such as hypertension, proteinuria, thrombocytopenia, elevated liver enzymes and increased angiogenic factors (soluble fms-like tyrosine kinase-1 to placental growth factor ratio [sFlt-1/PlGF]). A total of 106 women were admitted to Intensive Care Unit due to severe pneumonia and 68 were included in the study. Of those, 53 (50.0%) did not meet the diagnostic criteria for PE and remained pregnant after pneumonia (non-PE), seven (6.6%) met the diagnostic criteria for PE, had abnormal (>38) sFlt-1/PlGF (PE) and delivered during severe pneumonia, and eight (7.5%) met the diagnostic criteria for PE, had normal (≤38) sFlt-1/PlGF (PE-like) and did not deliver during pneumonia. Despite not having delivered, most PE-related features improved after severe pneumonia in women with PE-like syndrome. Women with PE had significantly poorer outcomes than women with PE-like syndrome or without PE. More than 50% of women with severe COVID-19 and diagnostic criteria for PE may not be PE but a PE-like syndrome, which may affect up to 7.5% of women with severe COVID-19. PE-like syndrome might have similar perinatal outcomes to those of normotensive women with severe pneumonia due to COVID-19. For these reasons, PE-like syndrome should be excluded by using sFlt-1/PlGF in future research and before making clinical decisions

Confirmation of preeclampsia-like syndrome induced by severe COVID-19: an observational study

COVID-19; Preeclampsia; PregnancyCOVID-19; Preeclampsia; EmbarazoCOVID-19; Preeclampsia; EmbaràsBACKGROUND Since the outbreak of the COVID-19 pandemic, some studies have reported an increased preeclampsia incidence in pregnant women with SARS-CoV-2 infection. Several explanations for this association have been proposed, including a preeclampsia-like syndrome induced by severe COVID-19. This syndrome was described in a small case series and has not been confirmed in larger studies, and its effect on perinatal outcomes has not been studied. OBJECTIVE This study aimed to confirm the preeclampsia-like syndrome because of COVID-19 and to investigate its implications on pregnancy outcomes and prognosis. STUDY DESIGN This was a prospective, observational study conducted in a tertiary referral hospital. The inclusion criteria were pregnant women admitted to the intensive care unit for severe pneumonia because of COVID-19. They were classified into 3 groups based on clinical and laboratory findings: preeclampsia, preeclampsia-like syndrome, and women without preeclampsia features. The 3 cohorts were analyzed and compared at 3 different times: before, during, and after severe pneumonia. The main outcomes were incidence of adverse perinatal outcomes and signs and symptoms of PE, such as hypertension, proteinuria, thrombocytopenia, elevated liver enzymes, and increased angiogenic factors (soluble fms-like tyrosine kinase 1–to–placental growth factor ratio). RESULTS A total of 106 women were admitted to the intensive care unit because of severe pneumonia, and 68 women were included in the study. Of those, 53 (50.0%) did not meet the diagnostic criteria for preeclampsia and remained pregnant after pneumonia (non-preeclampsia); 7 (6.6%) met the diagnostic criteria for preeclampsia, had abnormal (>38) soluble fms-like tyrosine kinase 1–to–placental growth factor ratio (preeclampsia), and delivered during severe pneumonia, and 8 (7.5%) met the diagnostic criteria for preeclampsia, had normal (≤38) soluble fms-like tyrosine kinase 1–to–placental growth factor ratio (preeclampsia like), and did not deliver during pneumonia. Despite not having delivered, most preeclampsia-related features improved after severe pneumonia in women with preeclampsia-like syndrome. Women with preeclampsia had significantly poorer outcomes than women with preeclampsia-like syndrome or without preeclampsia. CONCLUSION More than 50% of women with severe COVID-19 and diagnostic criteria for preeclampsia may not be preeclampsia but a preeclampsia-like syndrome, which may affect up to 7.5% of women with severe COVID-19. Preeclampsia-like syndrome might have similar perinatal outcomes to those of normotensive women with severe pneumonia because of COVID-19. For these reasons, preeclampsia-like syndrome should be excluded by using soluble fms-like tyrosine kinase 1–to–placental growth factor ratio in future research and before making clinical decisions

Design and implementation of a standard care programme of therapeutic exercise and education for breast cancer survivors

Background Breast cancer survivors (BCS) face several symptoms and are at higher risk of weight gain following diagnosis. Current literature shows that both exercise and diet play a key role in recovery of BCS. However, there is a gap between current guidelines and the real-world context. The aim of this article is to describe the process behind a free, not-for-proft community-based therapeutic exercise and education programme (TEEP) for BCS in the clinical setting. Methods The “Onco-Health Club” (OHC) consists of therapeutic exercise (TE) intervention aimed at ameliorating cancerrelated fatigue (CRF) and improving QoL and physical function. TE is supplemented with nutritional education, providing information about the Mediterranean diet. To this end, patients are recruited from an oncologist and are referred to a physiotherapist and a nutritionist for baseline assessment. TEEP consists of a 3-month intervention, delivered twice a week in a group format with 1 h of TE and 30 min of nutritional education. BCS then have a fnal assessment and are advised to continue with a healthy lifestyle. Data about referral, compliance and assessment were collected. Results From May 2017 to February of 2020, a total of 158 patients were recruited from 8 cohorts and 142 initially started the OHC. From 119 that joined the program, 96 patients were considered to have fnished it with good adherence (assistance>80%). BCS signifcantly improved their QoL, as well as upper and lower limb’s function, and increased their level of physical activity. CRF tended to decrease (p=0.005). Conclusions This study obtained data on recruitment, compliance, and possible limitations of these kinds of programmes in a real-world context. Further research is needed in order to optimize patient engagement and compliance, as well as to determine the transferability of these programmes in the clinical setting. Trial registration NCT03879096, Registered 18th March 2019. Retrospectively registered.Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. This research project was partially funded by Contract No. PS16060 in IBIMA between Novartis-IBIMA (Translation Research in Cancer B-01 & Clinimetric F-14) for the physiotherapist and the nutritionist in the assessment. Funding for open access charge: Universidad de Málaga / CBUA

Incident Use of Hydroxychloroquine for the Treatment of Rheumatoid Arthritis and Systemic Lupus Erythematosus During the COVID-19 Pandemic

Objective: We studied whether the use of hydroxychloroquine (HCQ) for COVID-19 resulted in supply shortages for patients with rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE). Methods: We used US claims data (IQVIA PHARMETRICS® Plus for Academics [PHARMETRICS]) and hospital electronic records from Spain (Institut Municipal d'Assistència Sanitària Information System [IMASIS]) to estimate monthly rates of HCQ use between January 2019 and March 2022, in the general population and in patients with RA and SLE. Methotrexate (MTX) use was estimated as a control. Results: More than 13.5 million individuals (13,311,811 PHARMETRICS, 207,646 IMASIS) were included in the general population cohort. RA and SLE cohorts enrolled 135,259 and 39,295 patients, respectively, in PHARMETRICS. Incidence of MTX and HCQ were stable before March 2020. On March 2020, the incidence of HCQ increased by 9- and 67-fold in PHARMETRICS and IMASIS, respectively, and decreased in May 2020. Usage rates of HCQ went back to prepandemic trends in Spain but remained high in the United States, mimicking waves of COVID-19. No significant changes in HCQ use were noted among patients with RA and SLE. MTX use rates decreased during HCQ approval period for COVID-19 treatment. Conclusion: Use of HCQ increased dramatically in the general population in both Spain and the United States during March and April 2020. Whereas Spain returned to prepandemic rates after the first wave, use of HCQ remained high and followed waves of COVID-19 in the United States. However, we found no evidence of general shortages in the use of HCQ for both RA and SLE in the United States.</p

Kinetics of humoral immune response over 17 months of COVID-19 pandemic in a large cohort of healthcare workers in Spain : the ProHEpiC-19 study

Understanding the immune response to the SARS-CoV-2 virus is critical for efficient monitoring and control strategies. The ProHEpic-19 cohort provides a fine-grained description of the kinetics of antibodies after SARS-CoV-2 infection with an exceptional resolution over 17 months. We established a cohort of 769 healthcare workers including healthy and infected with SARS-CoV-2 in northern Barcelona to determine the kinetics of the IgM against the nucleocapsid (N) and the IgG against the N and spike (S) of SARS-CoV-2 in infected healthcare workers. The study period was from 5 May 2020 to 11 November 2021.We used non-linear mixed models to investigate the kinetics of IgG and IgM measured at nine time points over 17 months from the date of diagnosis. The model included factors of time, gender, and disease severity (asymptomatic, mild-moderate, severe-critical) to assess their effects and their interactions. 474 of the 769 participants (61.6%) became infected with SARS-CoV-2. Significant effects of gender and disease severity were found for the levels of all three antibodies. Median IgM(N) levels were already below the positivity threshold in patients with asymptomatic and mild-moderate disease at day 270 after the diagnosis, while IgG(N and S) levels remained positive at least until days 450 and 270, respectively. Kinetic modelling showed a general rise in both IgM(N) and IgG(N) levels up to day 30, followed by a decay with a rate depending on disease severity. IgG(S) levels remained relatively constant from day 15 over time. IgM(N) and IgG(N, S) SARS-CoV-2 antibodies showed a heterogeneous kinetics over the 17 months. Only the IgG(S) showed a stable increase, and the levels and the kinetics of antibodies varied according to disease severity. The kinetics of IgM and IgG observed over a year also varied by clinical spectrum can be very useful for public health policies around vaccination criteria in adult population. Regional Ministry of Health of the Generalitat de Catalunya (Call COVID19-PoC SLT16_04; NCT04885478). The online version contains supplementary material available at 10.1186/s12879-022-07696-6

Estudio de factores predictivos de respuesta patológica a quimioterapia neoadyuvante en el cáncer de mama receptores hormonales positivos HER2 negativo

Se trata de un estudio de casos de carcinomas de mama con escasa información respecto a los factores que determinan la repuesta a quimioterapia neoadyuvante. Un elevado nivel de proliferación y el estado de receptores hormonales han mostrado ser predictivos de dicha respuesta.La quimioterapia neoadyuvante (QTN) se utiliza cada vez más para conseguir una reducción tumoral que permita una cirugía conservadora y, mediante el grado de respuesta patológica tumoral, determinar el pronóstico de las pacientes. Los datos anatomopatológicos proporcionados por la biopsia previa al tratamiento (BAG), podrían ser determinantes para conocer el grado de respuesta y estar relacionados con la evolución de la enfermedad. El objetivo del estudio es, determinar el valor predictivo de respuesta, basado en variables anatomopatológicas de la BAG, en una cohorte de 220 casos de mujeres con cáncer de mama fenotipo RE positivo y HER2 negativo, tratadas de 3 a 6 meses con antraciclina/taxanos, en 4 hospitales de Andalucía, desde el año 2003 al año 2014. El tamaño previo tumoral, el grado histológico, RE (receptores de estrógenos), RP (receptores de progesterona), nivel de proliferación (Ki67) y subtipo molecular subrrogado inmunohistoquímico, fueron evaluados en la BAG, y se compararon con el grado de respuesta a QTN en la pieza quirúrgica (sistemas de Miller y Payne [MyP] y RCB) valorado por un observador. Resultados: En nuestro estudio, los tumores con inmunoexpresión de RE 50% (p<0,05). Además, responden mejor al tratamiento los carcinoma con subtipo luminal B que los luminal A (p=0,04). Conclusiones: Además de un elevado nivel de proliferación, el estado de receptores de estrógenos y progesterona también influye en la respuesta a QTN en carcinoma de mama Her2 negativo, respondiendo mejor los pacientes con expresión hormonal baja. Probablemente relacionado con lo anterior, las pacientes con subtipo luminal B, mostratron una mejor respuesta.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech