89 research outputs found

    Proliferation and estrogen signaling can distinguish patients at risk for early versus late relapse among estrogen receptor positive breast cancers

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    Introduction: We examined if a combination of proliferation markers and estrogen receptor (ER) activity could predict early versus late relapses in ER-positive breast cancer and inform the choice and length of adjuvant endocrine therapy. Methods: Baseline affymetrix gene-expression profiles from ER-positive patients who received no systemic therapy (n = 559), adjuvant tamoxifen for 5 years (cohort-1: n = 683, cohort-2: n = 282) and from 58 patients treated with neoadjuvant letrozole for 3 months (gene-expression available at baseline, 14 and 90 days) were analyzed. A proliferation score based on the expression of mitotic kinases (MKS) and an ER-related score (ERS) adopted from Oncotype DX® were calculated. The same analysis was performed using the Genomic Grade Index as proliferation marker and the luminal gene score from the PAM50 classifier as measure of estrogen-related genes. Median values were used to define low and high marker groups and four combinations were created. Relapses were grouped into time cohorts of 0-2.5, 0-5, 5-10 years. Results: In the overall 10 years period, the proportional hazards assumption was violated for several biomarker groups indicating time-dependent effects. In tamoxifen-treated patients Low-MKS/Low-ERS cancers had continuously increasing risk of relapse that was higher after 5 years than Low-MKS/High-ERS cancers [0 to 10 year, HR 3.36; p = 0.013]. High-MKS/High-ERS cancers had low risk of early relapse [0-2.5 years HR 0.13; p = 0.0006], but high risk of late relapse which was higher than in the High-MKS/Low-ERS group [after 5 years HR 3.86; p = 0.007]. The High-MKS/Low-ERS subset had most of the early relapses [0 to 2.5 years, HR 6.53; p < 0.0001] especially in node negative tumors and showed minimal response to neoadjuvant letrozole. These findings were qualitatively confirmed in a smaller independent cohort of tamoxifen-treated patients. Using different biomarkers provided similar results. Conclusions: Early relapses are highest in highly proliferative/low-ERS cancers, in particular in node negative tumors. Relapses occurring after 5 years of adjuvant tamoxifen are highest among the highly-proliferative/high-ERS tumors although their risk of recurrence is modest in the first 5 years on tamoxifen. These tumors could be the best candidates for extended endocrine therapy

    International estimated fetal weight standards of the INTERGROWTH-21(st) Project.

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    OBJECTIVE: Estimated fetal weight (EFW) and fetal biometry are complementary measures used to screen for fetal growth disturbances. Our aim was to provide international EFW standards to complement the INTERGROWTH-21(st) Fetal Growth Standards that are available for use worldwide. METHODS: Women with an accurate gestational-age assessment, who were enrolled in the prospective, international, multicenter, population-based Fetal Growth Longitudinal Study (FGLS) and INTERBIO-21(st) Fetal Study (FS), two components of the INTERGROWTH-21(st) Project, had ultrasound scans every 5 weeks from 9-14 weeks' until 40 weeks' gestation. At each visit, measurements of fetal head circumference (HC), biparietal diameter, occipitofrontal diameter, abdominal circumference (AC) and femur length (FL) were obtained blindly by dedicated research sonographers using standardized methods and identical ultrasound machines. Birth weight was measured within 12 h of delivery by dedicated research anthropometrists using standardized methods and identical electronic scales. Live babies without any congenital abnormality, who were born within 14 days of the last ultrasound scan, were selected for inclusion. As most births occurred at around 40 weeks' gestation, we constructed a bootstrap model selection and estimation procedure based on resampling of the complete dataset under an approximately uniform distribution of birth weight, thus enriching the sample size at extremes of fetal sizes, to achieve consistent estimates across the full range of fetal weight. We constructed reference centiles using second-degree fractional polynomial models. RESULTS: Of the overall population, 2404 babies were born within 14 days of the last ultrasound scan. Mean time between the last scan and birth was 7.7 (range, 0-14) days and was uniformly distributed. Birth weight was best estimated as a function of AC and HC (without FL) as log(EFW) = 5.084820 - 54.06633 × (AC/100)(3)  - 95.80076 × (AC/100)(3)  × log(AC/100) + 3.136370 × (HC/100), where EFW is in g and AC and HC are in cm. All other measures, gestational age, symphysis-fundus height, amniotic fluid indices and interactions between biometric measures and gestational age, were not retained in the selection process because they did not improve the prediction of EFW. Applying the formula to FGLS biometric data (n = 4231) enabled gestational age-specific EFW tables to be constructed. At term, the EFW centiles matched those of the INTERGROWTH-21(st) Newborn Size Standards but, at < 37 weeks' gestation, the EFW centiles were, as expected, higher than those of babies born preterm. Comparing EFW cross-sectional values with the INTERGROWTH-21(st) Preterm Postnatal Growth Standards confirmed that preterm postnatal growth is a different biological process from intrauterine growth. CONCLUSIONS: We provide an assessment of EFW, as an adjunct to routine ultrasound biometry, from 22 to 40 weeks' gestation. However, we strongly encourage clinicians to evaluate fetal growth using separate biometric measures such as HC and AC, as well as EFW, to avoid the minimalist approach of focusing on a single value

    Variables with time-varying effects and the Cox model: Some statistical concepts illustrated with a prognostic factor study in breast cancer

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    International audienceBACKGROUND: The Cox model relies on the proportional hazards (PH) assumption, implying that the factors investigated have a constant impact on the hazard - or risk - over time. We emphasize the importance of this assumption and the misleading conclusions that can be inferred if it is violated; this is particularly essential in the presence of long follow-ups. METHODS: We illustrate our discussion by analyzing prognostic factors of metastases in 979 women treated for breast cancer with surgery. Age, tumour size and grade, lymph node involvement, peritumoral vascular invasion (PVI), status of hormone receptors (HRec), Her2, and Mib1 were considered. RESULTS: Median follow-up was 14 years; 264 women developed metastases. The conventional Cox model suggested that all factors but HRec, Her2, and Mib1 status were strong prognostic factors of metastases. Additional tests indicated that the PH assumption was not satisfied for some variables of the model. Tumour grade had a significant time-varying effect, but although its effect diminished over time, it remained strong. Interestingly, while the conventional Cox model did not show any significant effect of the HRec status, tests provided strong evidence that this variable had a non-constant effect over time. Negative HRec status increased the risk of metastases early but became protective thereafter. This reversal of effect may explain non-significant hazard ratios provided by previous conventional Cox analyses in studies with long follow-ups. CONCLUSIONS: Investigating time-varying effects should be an integral part of Cox survival analyses. Detecting and accounting for time-varying effects provide insights on some specific time patterns, and on valuable biological information that could be missed otherwise

    Garbage in, garbage out: how reliable training data improved a virtual screening approach against SARS-CoV-2 MPro

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    Introduction: The identification of chemical compounds that interfere with SARS-CoV-2 replication continues to be a priority in several academic and pharmaceutical laboratories. Computational tools and approaches have the power to integrate, process and analyze multiple data in a short time. However, these initiatives may yield unrealistic results if the applied models are not inferred from reliable data and the resulting predictions are not confirmed by experimental evidence.Methods: We undertook a drug discovery campaign against the essential major protease (MPro) from SARS-CoV-2, which relied on an in silico search strategy –performed in a large and diverse chemolibrary– complemented by experimental validation. The computational method comprises a recently reported ligand-based approach developed upon refinement/learning cycles, and structure-based approximations. Search models were applied to both retrospective (in silico) and prospective (experimentally confirmed) screening.Results: The first generation of ligand-based models were fed by data, which to a great extent, had not been published in peer-reviewed articles. The first screening campaign performed with 188 compounds (46 in silico hits and 100 analogues, and 40 unrelated compounds: flavonols and pyrazoles) yielded three hits against MPro (IC50 ≤ 25 μM): two analogues of in silico hits (one glycoside and one benzo-thiazol) and one flavonol. A second generation of ligand-based models was developed based on this negative information and newly published peer-reviewed data for MPro inhibitors. This led to 43 new hit candidates belonging to different chemical families. From 45 compounds (28 in silico hits and 17 related analogues) tested in the second screening campaign, eight inhibited MPro with IC50 = 0.12–20 μM and five of them also impaired the proliferation of SARS-CoV-2 in Vero cells (EC50 7–45 μM).Discussion: Our study provides an example of a virtuous loop between computational and experimental approaches applied to target-focused drug discovery against a major and global pathogen, reaffirming the well-known “garbage in, garbage out” machine learning principle

    Ki-67: level of evidence and methodological considerations for its role in the clinical management of breast cancer: analytical and critical review

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    Angioplastia transluminal percutánea en obstrucciones de vasos periféricos: análisis de resultados y seguimiento

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    La angioplastia transluminal percut&aacute;nea es un m&eacute;todo aceptado para el tratamiento de las obstrucciones de vasos perif&eacute;ricos.Percutaneous transluminal angioplasty (PTA) is a technic started more than 2 decades ago, has evolved considerably and, is a currently used method for the treatment of peripheral vascular disease
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