Respective Prognostic Value of Genomic Grade and Histological Proliferation Markers in Early Stage (pN0) Breast Carcinoma

Genomic grade (GG) is a 97-gene signature which improves the accuracy and prognostic value of histological grade (HG) in invasive breast carcinoma. Since most of the genes included in the GG are involved in cell proliferation, we performed a retrospective study to compare the prognostic value of GG, Mitotic Index and Ki67 score.A series of 163 consecutive breast cancers was retained (pT1-2, pN0, pM0, 10-yr follow-up). GG was computed using MapQuant Dx(R).GG was low (GG-1) in 48%, high (GG-3) in 31% and equivocal in 21% of cases. For HG-2 tumors, 50% were classified as GG-1, 18% as GG-3 whereas 31% remained equivocal. In a subgroup of 132 ER+/HER2- tumors GG was the most significant prognostic factor in multivariate Cox regression analysis adjusted for age and tumor size (HR = 5.23, p = 0.02).In a reference comprehensive cancer center setting, compared to histological grade, GG added significant information on cell proliferation in breast cancers. In patients with HG-2 carcinoma, applying the GG to guide the treatment scheme could lead to a reduction in adjuvant therapy prescription. However, based on the results observed and considering (i) the relatively close prognostic values of GG and Ki67, (ii) the reclassification of about 30% of HG-2 tumors as Equivocal GG and (iii) the economical and technical requirements of the MapQuant micro-array GG test, the availability in the near future of a PCR-based Genomic Grade test with improved performances may lead to an introduction in clinical routine of this test for histological grade 2, ER positive, HER2 negative breast carcinoma

Real versus sham proximal biofield therapy in the treatment of warts of the hands and feet in adults: study protocol for a randomized controlled trial (MAGNETIK study)

Abstract Background Despite the lack of scientific studies on biofield therapies, they are widely acclaimed by patients. The mechanisms of action are not explained by current allopathic medical approaches. Warts are common and contagious viral lesions that may be refractory to standard dermatologic treatments such as cryotherapy, laser therapy, and keratolytic ointments. Biofield therapies are efficient in various pathologies. Their ability to treat warts has never been demonstrated in a scientific study with a robust methodology. Patients with refractory warts often place their trust in these alternative therapies because of the poor results obtained from traditional medicine. We propose a prospective, randomized, single-blind, assessor-blind trial to evaluate the efficacy of treatment of warts by biofield therapy. Methods/design Subjects with warts on their feet or hands will be randomized into two groups: real biofield therapy versus sham therapy. The diagnosis will be made at the time of inclusion, and follow-up will take place in week 3. Comparison of pictures of the warts at baseline and after 3 weeks will be used as the primary outcome measure. The hypothesis is that the extent of the disappearance of the original wart in the group treated by real biofield therapy will be 70% and that it will be 30% in the group treated by sham therapy. Using 90% power and an alpha risk of 5%, 31 subjects are required in each group for a two-tailed proportion comparison test. Discussion To our knowledge, this is the first study to evaluate the efficacy of biofield therapy on warts. Therefore, the aim of this study is to extend knowledge of biofield therapy to another area of medicine such as dermatology and to propose complementary or alternative practices to improve patient well-being. The main strength of the study is that it is a randomized, single-blind, assessor-blind, placebo-controlled study. Trial registration ClinicalTrials.gov identifier: NCT02773719 . Registered on 22 April 2016

Development and clinical validation of real‐time artificial intelligence diagnostic companion for fetal ultrasound examination

International audienceABSTRACT Objective Prenatal diagnosis of a rare disease on ultrasound relies on a physician's ability to remember an intractable amount of knowledge. We developed a real‐time decision support system (DSS) that suggests, at each step of the examination, the next phenotypic feature to assess, optimizing the diagnostic pathway to the smallest number of possible diagnoses. The objective of this study was to evaluate the performance of this real‐time DSS using clinical data. Methods This validation study was conducted on a database of 549 perinatal phenotypes collected from two referral centers (one in France and one in the UK). Inclusion criteria were: at least one anomaly was visible on fetal ultrasound after 11 weeks' gestation; the anomaly was confirmed postnatally; an associated rare disease was confirmed or ruled out based on postnatal/postmortem investigation, including physical examination, genetic testing and imaging; and, when confirmed, the syndrome was known by the DSS software. The cases were assessed retrospectively by the software, using either the full phenotype as a single input, or a stepwise input of phenotypic features, as prompted by the software, mimicking its use in a real‐life clinical setting. Adjudication of discordant cases, in which there was disagreement between the DSS output and the postnatally confirmed (‘ascertained’) diagnosis, was performed by a panel of external experts. The proportion of ascertained diagnoses within the software's top‐10 differential diagnoses output was evaluated, as well as the sensitivity and specificity of the software to select correctly as its best guess a syndromic or isolated condition. Results The dataset covered 110/408 (27%) diagnoses within the software's database, yielding a cumulative prevalence of 83%. For syndromic cases, the ascertained diagnosis was within the top‐10 list in 93% and 83% of cases using the full‐phenotype and stepwise input, respectively, after adjudication. The full‐phenotype and stepwise approaches were associated, respectively, with a specificity of 94% and 96% and a sensitivity of 99% and 84%. The stepwise approach required an average of 13 queries to reach the final set of diagnoses. Conclusions The DSS showed high performance when applied to real‐world data. This validation study suggests that such software can improve perinatal care, efficiently providing complex and otherwise overlooked knowledge to care‐providers involved in ultrasound‐based prenatal diagnosis. © 2023 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology

How to attract doctors to careers in the fields of pharmaceutical medicine and medical devices?

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Use of genomic grade index to improve tumor grading of invasive lobular breast carcinoma.

info:eu-repo/semantics/nonPublishe

Adjuvant systemic treatment received by the patients in 1995–1996 and hypothetical treatment decision based on the Institut Curie (IC) 2010 guidelines.

<p>Treatment decision simulation was based on the histological grade (HG) or the Genomic Grade (GG). AHT: adjuvant hormonal therapy. ACT: adjuvant chemotherapy.</p