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Background Palbociclib and ribociclib are novel oral agents in hormone receptor-positive metastatic breast cancer. Neutropenia is a common adverse event associated with these treatments and its clinical management often requires regimen changes, such as cycle delays and dose adjustments. Objective To provide a real-world experience of the effectiveness and toxicities associated with these drugs and to evaluate the impact of regimen changes in disease progression. Setting This study was performed at Hospital Universitario La Paz, in Spain. Methods Observational, retrospective study which included hormone receptor-positive metastatic breast cancer patients who initiated treatment with palbociclib or ribociclib between March 1st, 2018 and March 1st, 2019. Main outcome measure The primary effectiveness variable was progression-free survival. Safety evaluation was performed to determine neutropenia-incidence and severity, as well as its clinical management, including dose adjustments and treatment interruptions. Correlations between these regimen changes and effectiveness were also evaluated. Results Sixty-one patients were included, 33 treated with palbociclib and 28 with ribociclib. Palbociclib was mainly used as second line of treatment in the metastatic setting (81.8%) and ribociclib as first line (67.9%). The median progression-free survival was 12.76 months (95% CI 7.5 to not estimable) in palbociclib and not reached in ribociclib. After 12 months, the progression-free survival rate was 51.5% (95% CI 34–69) in palbociclib and 78.6% (95% CI 63–94.1) in ribociclib. Neutropenia was the most common adverse event with an incidence rate of 87.9% in palbociclib and 82.1% in ribociclib. Cycle delays were needed in more than half of the patients treated with palbociclib and ribociclib (63.6% and 64.3%). Dose adjustments were seen in 42.4% and 53.6% of the patients receiving palbociclib and ribociclib, respectively. Regimen changes did not involve statistically significant differences in 12-month PFS rates in the cohort investigated. Conclusion Palbociclib and ribociclib outcomes are comparable to those reached in the phase III trials, PALOMA-3 and MONALEESA-2, respectively, and cannot be compared as they were used in different treatment settings. The toxicity profile is favourable, being neutropenia the most common adverse event, easily managed with regimen changes. Further studies are needed to confirm the observed tendency of no detrimental impact on effectiveness of these regimen changes.

Background:Difficult-to-manage (D2M) axial spondyloarthritis (axSpA) is an emerging concept, whose definition is yet to be established. The characterisation of these subgroup of patients is relevant, as it may contribute to a broader understanding of the reasons behind treatment failure and to the development of new therapeutic strategies [1].Objectives:To develop a predictive model to forecast patients from the early stages of treatment with b/tsDMARDs.Methods:We analysed data from an observational prospective cohort from La Paz Hospital between 2004-2019 which included patients diagnosed of axSpA initiating a b/tsDMARD, and who fulfilled one of these two definitions: a) D2M: failure to at least 2 b/tsDMARDs, b) good responders (GR): patients remaining their first bDMARD for at least 3 years or withdrawing it because of sustained disease control. Clinical, laboratory, therapy-related information and disease activity measures prior to starting the first b/tsDMARD (baseline), as well as disease activity measures 6-months after initiating it, were collected. Delta-ASDAS was estimated as the difference between baseline and 6-month ASDAS. After excluding the variables with the greater number of missing values, all the variables associated with D2M-axSpA in the univariable regression analyses were selected in order to create Classification And Regression Tree (CART) models. The cohort was randomly split into two independent groups: a training set (80%) and a validation set (20%). Later on, the CART model inputted the most associated factors with D2M-axSpA selecting an optimal cut-off point for classification. Subsequent splits were made, using the Gini index, to divide the population into two branches, until the terminal node. Finally, the model’s performance was assessed using the validation set.Results:Among the 101 patients included in the cohort, 41 (41.6%) were classified as D2M, 59 (58.4%) were male with a mean age of 43 years old. D2M patients were less frequently HLA-B27 positive, had more peripheral manifestations (enthesitis), extra-musculoskeletal manifestations (IBD), comorbidities, and scored higher in composite disease activity indices 6 months after starting a first bDMARD (but did not in baseline indices). Two different CART models were obtained, with a lesser number of patients included in the second model because of the missing values. These 2 models with their cut-off points and the probability of D2M axSpA after each step are shown in Figure 1. The first model (Figure 1, model a) had a pre-test probability of D2M of 44%, and identified BASDAI (cut-off point < 4) after 6 months of therapy with the first bDMARD and age at the beginning of the first bDMARD (cut-off point ≥ 44 years old) as the most relevant factors. The second model (Figure 1, model b) had a pre-test probability of D2M of 47%. It used delta-ASDAS (cut-off point ≥ 1.1) as the variable for the first step, and tender joint count (cut-off point < 1) after 6 months of therapy with the first bDMARD and baseline age (cut-off point ≥ 53) for the second step. After validation, the CART models achieved an AUC of 0.94 (95% CI 0.87-1) and 0.83 (95% CI 0.67-1), respectively, and both of them classified properly 83% of the patients.Conclusion:This study identified two predictive models, which may be applied using everyday information, and could identify D2M-axSpA patients only after the first 6 months of bDMARD therapy. Next step will involve further validation in an external cohort.REFERENCES:[1] Wendling D, Verhoeven F, Prati C. Is the Difficult-to-Treat (D2T) concept applicable to axial spondyloarthritis? Joint Bone Spine. 2023;90(3):105512.Figure 1.CART models predicting D2M-axSpA. The value at each node represents the most frequently expected outcome (D2M in red or GR in green).GR: good responders, D2M: difficult-to-manage, BASDAI: Bath Ankylosing Spondylitis Disease Activity, ASDAS: Ankylosing Spondylitis Disease Activity Score, TJC: tender joint count.Acknowledgements:NIL.Disclosure of Interests:Manuel Juárez: None declared, Diego Benavent Eli Lilly, Janssen and UCB Pharma, Victoria Navarro-Compán Eli Lilly, Janssen, MSD, Novartis, Pfizer and UCB Pharma, AbbVie, Eli Lilly, Galapagos, Moonlake, MSD, Novartis, Pfizer and UCB Pharma, AbbVie and Novartis, Mariana Díaz-Almirón: None declared, Marta Novella-Navarro UCB, Lilly, Galapagos and Janssen, Diana Peiteado: None declared, Alejandro Villalba Janssen, Irene Monjo-Henry Roche, Novartis, UCB and Gedeon Richter, Laura Nuño: None declared, Alejandro Balsa AbbVie, Amgen, Pfizer, Galapagos, Novartis, Gilead, BMS, Nordic, Sanofi, Sandoz, Lilly, UCB and Roche, Chamaida Plasencia-Rodríguez AbbVie, Pfizer, Novartis, Lilly and Roche.

Background Hypophosphatasia (HPP) is a rare and underdiagnosed condition characterized by deficient bone and teeth mineralization. The aim of this study was first, to evaluate the diagnostic utility of employing alkaline phosphatase (ALP) threshold levels to identify adults with variants in ALPL among individuals with persistently low ALP levels and second, to determine the value of also including its substrates (serum pyridoxal-5′-phosphate—PLP—and urinary phosphoetanolamine-PEA) for this purpose in order to create a biochemical algorithm that could facilitate the diagnostic work-up of HPP. Results The study population comprised 77 subjects with persistent hypophosphatasaemia. They were divided into two groups according to the presence (+GT) or absence (−GT) of pathogenic ALPL variants: 40 +GT and 37 −GT. Diagnostic utility measures were calculated for different ALP thresholds and Receiver Operating Characteristic (ROC) curves were employed to determine PLP and PEA optimal cut-off levels to predict the presence of variants. The optimal threshold for ALP was 25 IU/L; for PLP, 180 nmol/L and for PEA, 30 µmol/g creatinine. Biochemical predictive models were assessed using binary logistic regression analysis and bootstrapping machine learning technique and results were then validated. For ALP < 25 UI/L (model 1), the area under curve (AUC) and the 95% confidence intervals (CI) was 0.68 (95% CI 0.63–0.72) and it improved to 0.87 (95% CI 0.8–0.9), when PEA or PLP threshold levels were added (models 2 and 3), reaching 0.94 (0.91–0.97) when both substrates were included (model 4). The internal validation showed that the addition of serum PLP threshold levels to the model just including ALP improved significantly sensitivity (S) and negative predictive value (NPV) − 100%, respectively- with an accuracy (AC) of 93% in comparison to the inclusion of urinary PEA (S: 71%; NPV 75% and AC: 79%) and similar diagnostic utility measures as those observed in model 3 were detected when both substrates were added. Conclusions In this study, we propose a biochemical predictive model based on the threshold levels of the main biochemical markers of HPP (ALP < 25 IU/L and PLP > 180 nmol/L) that when combined, seem to be very useful to identify individuals with ALPL variants.

Background Tracheostomy is one of the most frequent techniques in intensive care units (ICU). Fiberoptic bronchoscopy (FB) is a safety measure when performing a percutaneous dilatational tracheostomy (PDT), but the controversy surrounding the routine use of FB as part of the procedure remains open. National surveys in some European countries showed that the use of FB is non-standardized. Retrospective studies have not shown a significant difference in complications between procedures performed with or without a bronchoscope. International guidelines have not been able to establish recommendations regarding the use of FB in PDT due to lack of evidence. Design This is a multicenter (three centers at the time of  publishing this paper) randomized controlled clinical trial to examine the safety of percutaneous tracheostomy using FB. We will include all consecutive adult patients admitted to the ICU in whom percutaneous tracheostomy for prolonged mechanical ventilation is indicated and with no exclusion criteria for using FB. Eligible patients will be randomly assigned to receive blind PDT or PDT under endoscopic guidance. All procedures will be performed by experienced intensivists in PDT and FB. A Data Safety and Monitoring Board (DSMB) will monitor the trial. The primary outcome is the incidence of perioperative complications. Discussion FB is a safe technique when performing PDT although its use is not universally accepted in all ICUs as a routine practice. Should PDT be monitored routinely with endoscopic guidance? This study will assess the role of FB monitoring during PDT. Trial registration ClinicalTrials.gov NCT04265625. Registered on February 11, 2020

We investigated B-cell-activating factor (BAFF) in relation to response to treatment with TNF inhibitors (TNFis) in rheumatoid arthritis (RA). This was a longitudinal study including 158 patients with RA treated with TNFis and followed up for 6 months. Clinical response at 6 months of treatment was defined according to the EULAR criteria for good responders (GRs). BAFF concentration was measured in serum samples, collected at baseline and at 6 months. Associations with EULAR response were evaluated using univariable and multivariable logistic regression models. ROC analysis was performed to determine the optimal threshold of serum BAFF concentration associated with good EULAR response to treatment. After 6 months of TNFi treatment, 24% of patients were GRs. They had a lower BMI, lower baseline DAS28 and lower baseline serum BAFF concentration than non-responders. After 6 months of TNFi treatment, autoantibody-positive patients who attained GR had significantly lower serum BAFF concentrations compared with patients who did not. Serum BAFF < 968 pg/mL at 6 months represented the concentration likely to best discriminate between GR and non-GR at 6 months of TNFi treatment. Autoantibody-seropositive patients who had serum BAFF < 968 pg/mL at 6 months demonstrated a more than four-fold increased probability to be GRs compared with patients with higher BAFF concentrations. In conclusion, serum BAFF concentrations were associated with response to TNFis in seropositive RA patients, corroborating the importance of the B-cell compartment in RA.

Recent prospective studies support the feasibility of performing sentinel lymph node biopsy following neoadjuvant chemotherapy in initially fine-needle aspiration cytology or ultrasound-guided biopsy-proven node-positive breast cancer. The main aid is to identify preoperative features that help us predict a complete axillary response to neoadjuvant chemotherapy in these patients and thus select the candidates for sentinel lymph node biopsy post-neoadjuvant chemotherapy to avoid unnecessary axillary lymphadenectomy. A retrospective observational study with a total of 150 patients, biopsy-proven node-positive breast cancer who underwent neoadjuvant chemotherapy followed by breast surgery and axillary lymphadenectomy were included and retrospectively analysed. A predictive model was generated by a multivariate logistic regression analysis for pathological complete response-dependent variable. The response of the primary lesion to neoadjuvant chemotherapy according to post-treatment magnetic resonance imaging, Her2/neu overexpression and a low estrogen receptor expression are associated with a higher rate of nodal pathologically complete response. The multivariant model generated a receiver operating characteristic curve with an area under the curve of 0.79 and a confidence interval of 0.72-0.87 at a 95% level of significance. This model could be a helpful tool for the surgeon to help in predicting which cases have a higher likelihood of achieving a pathologically complete response and therefore selecting those who may benefit from a post-neoadjuvant chemotherapy sentinel lymph node biopsy and avoid unnecessary axillary lymphadenectomy.

BackgroundThere isn’t universal agreement regarding streptococcal pharyngitis, still considered rare below age 3 years.AimsTo study prevalence variations by age, season and clinical data. To test Centor and McIsaac scores and seek a better predictive model.MethodsWe retrospectively reviewed all clinical records of the patients seen in our hospital in 2011 selecting those in whom a throat swab for rapid antigen detection test or throat culture was collected to study prevalence and those with pharyngitis or scarlet fever diagnosis without throat swab to test score application effect on antibiotic prescription.ResultsGABHS prevalence: 28.3%, 1303 children included (aged 58 days-13 years), without seasonality:Abstract PO-0247 Table 1 MonthsYearsAge0–1112–232345678910111213% pyogenes12.211.828.536.034.833.831.434.517.941.916.133.313.321.4N491872212391611308658394331301514Abstract PO-027 Figure 1Centor and McIsaac scores didn’t differ between those with and without GABHS The best puctuation system we found, by logistic regression analysis, can predict GABHS with ROC 0.738 (95% CI: 0.702–0.772) combining age ≥3 years, scarlatiniform rash, palatal petechiae, lower temperature and absence of cough, but is complex. Its use without throat swab would’ve decreased antibiotic prescription at most 11–12% in this setting.ConclusionsGABHS seems more prevalent below age 3 years than commonly considered. Seasonality isn’t clear. Neither Centor nor McIsaac score was valid here, but finding a simple and better predictive model is complicated.

Advanced oxidation protein products (AOPPs) are considered as markers and even mediators of the proinflammatory effect of oxidative stress in uremia. We hypothesized that an increase of oxidative stress associated with peritoneal dialysis (PD), estimated by the variation of plasma AOPPs over time, might be associated with cardiovascular (CV) risk and overall prognosis. In 48 PD patients, blood samples were collected on two occasions: the first one in the first six months after starting PD therapy and the second one, one year after. The plasma AOPPs level variation over the first year on PD was significantly associated with CV antecedents and also with CV prognosis. In those patients in whom the AOPPs levels increased more than 50% above the baseline value, a significant association with past and future CV disease was confirmed. These patients had 4.7 times greater risk of suffering later CV disease than those with a smaller increase, even after adjusting for previous CV history. Our data suggest that the increase of AOPPs plasma level over the first year on PD is conditioned by CV antecedents but also independently predicts CV prognosis. AOPPs plasma levels seem to represent the CV status of PD patients with sufficient sensitivity to identify those with a clearly sustained higher CV risk.

Triple-negative breast cancer is a heterogeneous disease characterized by a lack of hormonal receptors and HER2 overexpression. It is the only breast cancer subgroup that does not benefit from targeted therapies, and its prognosis is poor. Several studies have developed specific molecular classifications for triple-negative breast cancer. However, these molecular subtypes have had little impact in the clinical setting. Gene expression data and clinical information from 494 triple-negative breast tumors were obtained from public databases. First, a probabilistic graphical model approach to associate gene expression profiles was performed. Then, sparse k-means was used to establish a new molecular classification. Results were then verified in a second database including 153 triple-negative breast tumors treated with neoadjuvant chemotherapy. Clinical and gene expression data from 494 triple-negative breast tumors were analyzed. Tumors in the dataset were divided into four subgroups (luminal-androgen receptor expressing, basal, claudin-low and claudin-high), using the cancer stem cell hypothesis as reference. These four subgroups were defined and characterized through hierarchical clustering and probabilistic graphical models and compared with previously defined classifications. In addition, two subgroups related to immune activity were defined. This immune activity showed prognostic value in the whole cohort and in the luminal subgroup. The claudin-high subgroup showed poor response to neoadjuvant chemotherapy. Through a novel analytical approach we proved that there are at least two independent sources of biological information: cellular and immune. Thus, we developed two different and overlapping triple-negative breast cancer classifications and showed that the luminal immune-positive subgroup had better prognoses than the luminal immune-negative. Finally, this work paves the way for using the defined classifications as predictive features in the neoadjuvant scenario.

Background Metabolomics has a great potential in the development of new biomarkers in cancer and it has experiment recent technical advances. Methods In this study, metabolomics and gene expression data from 67 localized (stage I to IIIB) breast cancer tumor samples were analyzed, using (1) probabilistic graphical models to define associations using quantitative data without other a priori information; and (2) Flux Balance Analysis and flux activities to characterize differences in metabolic pathways. Results On the one hand, both analyses highlighted the importance of glutamine in breast cancer. Moreover, cell experiments showed that treating breast cancer cells with drugs targeting glutamine metabolism significantly affects cell viability. On the other hand, these computational methods suggested some hypotheses and have demonstrated their utility in the analysis of metabolomics data and in associating metabolomics with patient’s clinical outcome. Conclusions Computational analyses applied to metabolomics data suggested that glutamine metabolism is a relevant process in breast cancer. Cell experiments confirmed this hypothesis. In addition, these computational analyses allow associating metabolomics data with patient prognosis.