4 research outputs found

    Phase I prognostic online (PIPO): A web tool to improve patient selection for oncology early phase clinical trials

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    Immunotherapy; Phase 1 trials; Prognostic modelInmunoterapia; Ensayos de fase 1; Modelo pronĂłsticoImmunoterĂ pia; Assajos de fase 1; Model pronĂČsticPurpose Patient selection in phase 1 clinical trials (Ph1t) continues to be a challenge. The aim of this study was to develop a user-friendly prognostic calculator for predicting overall survival (OS) outcomes in patients to be included in Ph1t with immune checkpoint inhibitors (ICIs) or targeted agents (TAs) based on clinical parameters assessed at baseline. Methods Using a training cohort with consecutive patients from the VHIO phase 1 unit, we constructed a prognostic model to predict median OS (mOS) as a primary endpoint and 3-month (3m) OS rate as a secondary endpoint. The model was validated in an internal cohort after temporal data splitting and represented as a web application. Results We recruited 799 patients (training and validation sets, 558 and 241, respectively). Median follow-up was 21.2 months (m), mOS was 10.2 m (95% CI, 9.3–12.7) for ICIs cohort and 7.7 m (95% CI, 6.6–8.6) for TAs cohort. In the multivariable analysis, six prognostic variables were independently associated with OS – ECOG, number of metastatic sites, presence of liver metastases, derived neutrophils/(leukocytes minus neutrophils) ratio [dNLR], albumin and lactate dehydrogenase (LDH) levels. The phase 1 prognostic online (PIPO) calculator showed adequate discrimination and calibration performance for OS, with C-statistics of 0.71 (95% CI 0.64–0.78) in the validation set. The overall accuracy of the model for 3m OS prediction was 87.2% (95% CI 85%–90%). Conclusions PIPO is a user-friendly objective and interactive tool to calculate specific survival probabilities for each patient before enrolment in a Ph1t. The tool is available at https://pipo.vhio.net/.The research leading to these results has received funding from “la Caixa” Foundation (LCF/PR/CE07/50610001). Cellex Foundation for providing research facilities and equipment. This work was supported by the Accelerator Award (UpSMART) from Fundacion CientĂ­fica – Asociacion Espanola Contra el Cancer (FC -AECC)/ Associazione Italiana per la Ricerca sul Cancro (AIRC) /Cancer Research United Kingdom (CRUK)

    Lupus en Argentina. Pacientes no respondedores al tratamiento estándar y belimumab como posible opción. Datos del registro RELESSAR

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    IntroducciĂłn: el lupus es una enfermedad compleja y varias veces de difĂ­cil abordaje. Alcanzar la remisiĂłn es uno de los objetivos, incorporando opciones terapĂ©uticas. Objetivos: describir las caracterĂ­sticas generales de los pacientes segĂșn el estado de la enfermedad y el uso de belimumab. Materiales y mĂ©todos: estudio de corte transversal, registro RELESSAR. Se definiĂł el estado de la enfermedad como: remisiĂłn: SLEDAI=0 y sin corticoides; baja actividad de la enfermedad: SLEDAI >0 y ≀4 y sin corticoides; control no Ăłptimo: SLEDAI >4 y cualquier dosis de corticoides. Resultados: se incluyeron 1.277 pacientes, 23,4% en remisiĂłn, 12,6% en baja actividad y 63,8% con control no Ăłptimo. En este Ășltimo grupo eran mĂĄs jĂłvenes y con menor duraciĂłn de la enfermedad; presentaban mayores Ă­ndices de actividad y cronicidad, y mayor empleo de inmunosupresores. Solo el 22,3% de los pacientes con criterio potencial de uso de belimumab (lupus eritematoso sistĂ©mico activo a pesar del tratamiento estĂĄndar) lo recibĂ­a en ese momento. Las variables asociadas a hospitalizaciones fueron: terapia con corticoides, ciclofosfamida y mayor SLICC. Conclusiones: se refleja la complejidad del manejo de estos pacientes y se visualizan aspectos estructurales como la desigualdad. El uso del belimumab resultarĂ­a beneficioso en los pacientes seleccionados

    Prospecting phosphate solubilizing bacteria in alkaline-sodic environments reveals intra-specific variability in Pantoea eucalypti affecting nutrient acquisition and rhizobial nodulation in Lotus tenuis

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    A bioprospecting study in alkaline-sodic soils of the Argentinean flooding pampa was performed in order to identify and characterize rhizospheric bacteria associated to Lotus tenuis plants, capable of solubilizing phosphate under a broad range of alkaline-sodic conditions. Our analysis, supported by repetitive BOX element based PCR and 16S rRNA sequences, identified 74 strains. All of them belong to the Phylum Proteobacteria, specifically to the order Enterobacteriales, and Pseudomonadales, suggesting that in this environment, broad pH-range P-solubilizing bacteria (BRPSB) associated to L. tenuis, are grouped within a narrow taxonomic range. A subsequent objective was to focus in a subgroup of BRPSB strains belonging to the Pantoea eucalypti species (MA66, P63, P76, P163, P173 and a formerly identified isolate, M91) that also produced siderophores, indol-acetic acid and showed invitro compatibility with the native rhizobial strain Mesorhizobium sanjuanii BSA136. Growth promoting effects of these P. eucalypti strains on L. tenuis plants in alkaline-sodic soils in symbiosis with the above mentioned rhizobial strain were analyzed. Despite all the P. eucalypti BRPSB strains exhibited the above-mentioned features, they exerted differential effects on plant growth and dry matter allocation to the nodules. Plants inoculated with P. eucalypti M91 displayed a superior capability to accumulate nitrogen, phosphorus and zinc. On the contrary, nodules dry matter allocation, and mineral nutrient accumulation in L. tenuis plants were negatively affected by P. eucalypti P76 compared with M91. Results hereby presented highlight the complexity of plant-microbe interactions and reveal that growth-promoting effects of P-solubilizing P. eucalypti strains cannot be predicted only on the basis of their in vitro PGPR features, complementary in planta assays being necessary for efficient strainselection. This study provides valuable information for biofertilization of L. tenuis plants in the flooding pampa.Fil: Cumpa VelĂĄsquez, Liz Marjory Stefanny. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Centro CientĂ­fico TecnolĂłgico Conicet - La Plata. Instituto de Investigaciones BiotecnolĂłgicas. Instituto de Investigaciones BiotecnolĂłgicas "Dr. RaĂșl AlfonsĂ­n" (sede ChascomĂșs). Universidad Nacional de San MartĂ­n. Instituto de Investigaciones BiotecnolĂłgicas. Instituto de Investigaciones BiotecnolĂłgicas "Dr. RaĂșl AlfonsĂ­n" (sede ChascomĂșs); ArgentinaFil: Moriconi, Jorge Ignacio. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Centro CientĂ­fico TecnolĂłgico Conicet - La Plata. Instituto de Investigaciones BiotecnolĂłgicas. Instituto de Investigaciones BiotecnolĂłgicas "Dr. RaĂșl AlfonsĂ­n" (sede ChascomĂșs). Universidad Nacional de San MartĂ­n. Instituto de Investigaciones BiotecnolĂłgicas. Instituto de Investigaciones BiotecnolĂłgicas "Dr. RaĂșl AlfonsĂ­n" (sede ChascomĂșs); ArgentinaFil: Dip, Diana Patricia. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Centro CientĂ­fico TecnolĂłgico Conicet - La Plata. Instituto de Investigaciones BiotecnolĂłgicas. Instituto de Investigaciones BiotecnolĂłgicas "Dr. RaĂșl AlfonsĂ­n" (sede ChascomĂșs). Universidad Nacional de San MartĂ­n. Instituto de Investigaciones BiotecnolĂłgicas. Instituto de Investigaciones BiotecnolĂłgicas "Dr. RaĂșl AlfonsĂ­n" (sede ChascomĂșs); ArgentinaFil: Castagno, Luis Nazareno. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Centro CientĂ­fico TecnolĂłgico Conicet - La Plata. Instituto de Investigaciones BiotecnolĂłgicas. Instituto de Investigaciones BiotecnolĂłgicas "Dr. RaĂșl AlfonsĂ­n" (sede ChascomĂșs). Universidad Nacional de San MartĂ­n. Instituto de Investigaciones BiotecnolĂłgicas. Instituto de Investigaciones BiotecnolĂłgicas "Dr. RaĂșl AlfonsĂ­n" (sede ChascomĂșs); ArgentinaFil: Puig, Maria Lucrecia. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Centro CientĂ­fico TecnolĂłgico Conicet - La Plata. Instituto de Investigaciones BiotecnolĂłgicas. Instituto de Investigaciones BiotecnolĂłgicas "Dr. RaĂșl AlfonsĂ­n" (sede ChascomĂșs). Universidad Nacional de San MartĂ­n. Instituto de Investigaciones BiotecnolĂłgicas. Instituto de Investigaciones BiotecnolĂłgicas "Dr. RaĂșl AlfonsĂ­n" (sede ChascomĂșs); ArgentinaFil: Maiale, Santiago Javier. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Centro CientĂ­fico TecnolĂłgico Conicet - La Plata. Instituto de Investigaciones BiotecnolĂłgicas. Instituto de Investigaciones BiotecnolĂłgicas "Dr. RaĂșl AlfonsĂ­n" (sede ChascomĂșs). Universidad Nacional de San MartĂ­n. Instituto de Investigaciones BiotecnolĂłgicas. Instituto de Investigaciones BiotecnolĂłgicas "Dr. RaĂșl AlfonsĂ­n" (sede ChascomĂșs); ArgentinaFil: Santa Maria, Guillermo Esteban. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Centro CientĂ­fico TecnolĂłgico Conicet - La Plata. Instituto de Investigaciones BiotecnolĂłgicas. Instituto de Investigaciones BiotecnolĂłgicas "Dr. RaĂșl AlfonsĂ­n" (sede ChascomĂșs). Universidad Nacional de San MartĂ­n. Instituto de Investigaciones BiotecnolĂłgicas. Instituto de Investigaciones BiotecnolĂłgicas "Dr. RaĂșl AlfonsĂ­n" (sede ChascomĂșs); ArgentinaFil: Sannazzaro, AnalĂ­a InĂ©s. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Centro CientĂ­fico TecnolĂłgico Conicet - La Plata. Instituto de Investigaciones BiotecnolĂłgicas. Instituto de Investigaciones BiotecnolĂłgicas "Dr. RaĂșl AlfonsĂ­n" (sede ChascomĂșs). Universidad Nacional de San MartĂ­n. Instituto de Investigaciones BiotecnolĂłgicas. Instituto de Investigaciones BiotecnolĂłgicas "Dr. RaĂșl AlfonsĂ­n" (sede ChascomĂșs); ArgentinaFil: Estrella, Maria Julia. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas. Centro CientĂ­fico TecnolĂłgico Conicet - La Plata. Instituto de Investigaciones BiotecnolĂłgicas. Instituto de Investigaciones BiotecnolĂłgicas "Dr. RaĂșl AlfonsĂ­n" (sede ChascomĂșs). Universidad Nacional de San MartĂ­n. Instituto de Investigaciones BiotecnolĂłgicas. Instituto de Investigaciones BiotecnolĂłgicas "Dr. RaĂșl AlfonsĂ­n" (sede ChascomĂșs); Argentin

    Predictability of adverse outcomes in hypertensive disorders of pregnancy: a multicenter prospective cohort study

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    Objectives To explore variables associated with adverse maternal/fetal/neonatal outcomes among pregnant/postpartum patients admitted to ICU for hypertensive disorders of pregnancy (HDP). Methods Multicenter, prospective, national cohort study. Results Variables independently associated with maternal/fetal/neonatal mortality among 172 patients were as follows: Acute Physiology and Chronic Health Evaluation-II (APACHE-II)(OR1.20[1.06–1.35]), gestational age (OR0.698[0.59–0.82]) and aspartate aminotransferase (AST)(OR1.004[1.001–1.006]). Positive likelihood ratio for headache, epigastric pain, and visual disturbances to predict composite adverse outcomes were 1.23(1.16–1.30), 0.76(0.59–1.02), and 1.1(0.98–1.2), respectively. Conclusions Maternal/fetal mortality due to HDP was independently associated with severity of illness on admission, gestational age, and elevated AST. Accuracy of clinical symptoms to predict composite adverse outcomes was low
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