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

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

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 pain catastrophizing scale on breast cancer survivor

Introduction: Pain catastrophizing scale (PCS) is the most used scale to measure pain catastrophizing. In breast cancer survivors (BCS), pain catastrophizing is related to upper-limbs dysfunction and disability. This study aimed to assess the internal consistency, internal structure, and convergent validity of the Spanish version of the PCS in Spanish BCS. Material and Methods: Breast cancer survivors were recruited from the service of Medical Oncology of the University Clinical Hospital Virgen de la Victoria, in Málaga (Spain). The psychometric properties were evaluated with analysis factor structure by maximum likelihood extraction (MLE), internal consistency, and construct validity by confirmatory factor analysis (CFA). Results: Factor structure was three-dimensional, and one item was removed due to cross-loading. The new 12-item PCS showed a high internal consistency for the total score (α = 0.91) and a good homogeneity, and CFA revealed a satisfactory fit. PCS showed an acceptable correlation with FACS (r =0.53, p <0.01). Conclusion: Pain catastrophizing scale is a valid and reliable instrument to evaluate pain catastrophizing in Spanish BCS. This tool may help clinicians in the management of pain by assessing pain and by measuring the effect of interventions.This work was partially supported by Novartis Oncology [Contract N° PS16060 in IBIMA between Novartis-IBIMA, (Translation Research in Cancer B-01 & Clinimetric F-14)]. Funding for open access charge: Universidad de Málaga / CBU

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

Forearm Muscle Activity During the Handgrip Test in Breast Cancer Survivors: A Cross-Sectional Study

We recruited 102 breast cancer survivors at a secondary care in Malaga. Included breast cancer survivors showed a good upper limb functionality but a reduced forearm muscle activity. Forearm muscle activity showed a poor significant correlation with the cancer-related fatigue . Handgrip strength also showed a poor correlation with the upper limb functionality. Both outcomes tended to lower values with higher levels of cancer-related fatigue. Introduction/Background: Breast cancer survivors (BCS) frequently show upper limb dysfunctions. The forearm muscle activity measured by surface electromyography (sEMG) in this population has not been studied. This study aimed to describe forearm muscle activity in BCS, as well as to assess its possible relationship with other variables related to upper limb functionality and cancer-related fatigue (CRF). Materials and Methods: A cross-sectional study was carried out including 102 BCS as volunteers at a secondary care in Malaga, Spain. BCS were included if they were aged between 32 and 70 years old, without evidence of cancer recurrence at the time of recruitment. The forearm muscle activity (microvolts, μV) was assessed by sEMG during the handgrip test. The handgrip strength was assessed by dynamometry (kg), the upper limb functionality (%) was measured by the upper limb functional index (ULFI) question- naire and the CRF was also assessed by revised Piper Fatigue Scale (0-10 points). Results: BCS reported reduced forearm muscle activity (287.88 μV) and reduced handgrip strength (21.31 Kg), a good upper limb functionality (68.85%), and a moderate cancer-related fatigue (4.74). Forearm muscle activity showed a poor significant correlation (r = –0.223, P = .038) with the CRF. Handgrip strength showed a poor correlation with the upper limb functionality (r = 0.387, P < .001) and age (r=-0.200, P = .047)...Funding for open access charge: Universidad de Málaga /CBU

Targeted therapies in the treatment of germ cell tumors: The need for new approaches against “orphan” tumors

Este artículo ha sido publicado en la revista Critical Reviews in Oncology/Hematology Esta versión tiene Licencia Creative Commons CC-BY-NC-NDGerm cell tumors (GCTs) are a heterogeneous group of tumors that are highly clinically relevant to oncologists. GCTs are generally highly sensitive to cisplatin-based chemotherapy and represent a model for curable neoplasms. Cisplatin-based combination therapy followed by surgical resection of the residual tumor is the cornerstone for GCTs treatment. Although the overall cure rate is high for patients with GCTs, patients with a poor prognosis according to International Consensus Criteria or with chemoresistant disease remain a major clinical challenge. Currently, between 15% and 20% of patients with metastatic disease still progress and will die as a consequence of the disease. Therefore, the discovery of new treatment strategies or new drugs based on translational oncology remains a priority for the treatment of patients with cisplatin-refractory disease and those with a poor prognosis. Clinical trials with new targeted therapies are ongoing for the treatment of GCTs. In this article, we review some of the new targeted biologic therapies that act on the most relevant oncogenesis pathways and are in clinical development for the treatment of GCT

Serum protein levels following surgery in breast cancer patients: A protein microarray approach

Este artículo ha sido publicado en INTERNATIONAL JOURNAL OF ONCOLOGY No hemos podido encontrar infomración sobre si permite depositar conlicencia creative Commons El archivo solicitado a la editorial como postprint que nos ha remitido es el que depositamosSurgery is the primary treatment for non-metastatic breast cancer. However, the risk of early recurrence remains after surgical removal of the primary tumor. Recurrence is suggested to result from hidden micrometastatic foci, which are triggered to escape from dormancy by surgical resection of the primary tumor. In this study, we focused on the differential impact of breast surgery on the serum profiles of early breast cancer patients and healthy women. Serum samples from invasive breast cancer patients, in situ carcinoma breast cancer patients and healthy women were analyzed using reverse phase protein array technology. Samples were collected prior to breast surgery and 24 h following breast surgery. Both the expression level and the velocity of 42 serum proteins were quantified and compared among groups. We found that surgery increased the concentration of several proteins (CSF1, THSB2, IL6, IL7, IL16, FasL and VEGF-B) in the overall population. Compared with healthy women and patients with non-invasive tumors, invasive tumor patients exhibited higher preoperative levels of several serum proteins, such as αFP, IFNβ1, VEGF-A, IL18, E-cadherin or CD31, and lower postoperative levels of TNFα and IL5. Similarly, we detected significant surgery-induced changes in the velocity of VEGF-A and IL16 accumulation in samples derived from invasive breast cancer patients. In conclusion, breast surgery induced distinct changes in the concentrations and dynamics of serum proteins in invasive breast cancer patients compared with healthy women and noninvasive tumor patients.The authors acknowledge support through grants from the Junta de Andalucia (0199/2006 and TIC-4026), the Fundacion Mutua Madrileña and the Spanish MINECO (TIN2010-16556)

A Carboxylesterase 2 Gene Polymorphism as Predictor of Capecitabine on Response and Time to Progression

Este artículo ha sido publicado en la revista Current Drug Metabolism Esta versión tiene Licencia Creative Commons CC-BY-NC-ND Le remito pdf recibido de mi solicitud a la revista del postprint, y que me han enviado por correo electrónico con permiso para su depósito.Capecitabine is a drug that requires the consecutive action of three enzymes: carboxylesterase 2 (CES 2), cytidine deaminase (CDD), and thymidine phosphorylase (TP) for transformation into 5-fluorouracil (5FU). The metabolism of 5FU requires the activity of thymidylate synthase (TS) and dihydropyrimidine dehydrogenase (DPD) among other enzymes. The present study prospectively examined the possible relationship between the toxicity and efficacy of capecitabine and 14 different polymorphisms in CES 2, CDD, TS and DPD. Between 2003 and 2005, a total of 136 patients with advanced breast or colorectal cancer treated with capecitabine were prospectively enrolled. The presence of two polymorphisms (CDD 943insC and CES 2 Exon3 6046 G/A) were associated with a non-statistically significant higher incidence of grade 3 hand-foot syndrome (HFS) (p=0.07) and grade 3-4 diarrhoea (p=0.09), respectively. Patients heterozygous or homozygous for the polymorphism CES 2 5’UTR 823 C/G exhibited a significantly greater response rate to capecitabine, and time to progression of disease (59%, 8.7 months) than patients with the wild type gene sequence (32%, p=0.015; 5.3 months, p=0.014). For the first time, an association between a polymorphism in the CES2 gene and the efficacy of capecitabine has been described, providing preliminary evidence of its predictive and prognostic value

Subtipado molecular del cáncer de mama masculino con PAM50: Correlación con el subtipaje inmunohistoquímico y estudio de supervivencia.

Introducción: El cáncer de mama masculino es una enfermedad rara aún poco conocida, que principalmente corresponde a subtipo luminal usando la clasificación molecular subrogada a inmunohistoquímica. En este estudio, se evalúa por primera vez la correlación entre los subtipos moleculares basados en un panel inmunohistoquímico de seis marcadores y el obtenido mediante la firma PAM50 en el cáncer de mama masculino, así como la evolución clínica de los diferentes subtipos encontrados. Material y métodos: Se recogieron 67 muestras quirúrgicas de cáncer de mama masculino invasivo de cuatro diferentes Servicios de Anatomía Patológica. La tinción inmunohistoquímica se realizó sobre tissue-microarrays, con un panel de seis marcadores (RE, RP, Her2, Ki67, CK 5-6 y EGFR). Los subtipos de PAM50 se determinaron mediante nCounter Analysis System. Se estudió la asociación entre los subtipos obtenidos mediante inmunohistoquímica y los determinados por PAM50, así como la supervivencia global y la supervivencia libre de enfermedad en los diferentes subtipos de cada clasificación. Resultados: La distribución de los subtipos moleculares tumorales según PAM50 fue: 60% luminal B, 30% luminal A y 10% Her2-enriched. Sólo uno de los tumores Her2-enriched también fue detectado por inmunohistoquímica y tratado con trastuzumab. No se obtuvo ningún tumor de subtipo basal-like. Utilizando la clasificación inmunohistoquímica, 51% de los tumores fueron luminal B, 43% luminal A, 3,5% triple negativo y 1,5% Her2-positivo. Las características clínico-patológicas no difirieron significativamente entre los subtipos inmunohistoquímicos y PAM50. Se observó una supervivencia global menor en los tumores Her2-enriched comparados con los luminales. Conclusión: El cáncer de mama masculino es principalmente una enfermedad genómica luminal con un predominio del subtipo luminal B. Además, se observaron casos de pacientes Her2-negativos por inmunohistoquímica, pero de perfil Her2-enriched por PAM50, con peor evolución clínica comparado con el subtipo luminal, que podrían haberse beneficiado de terapia anti-Her2.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech