Key Points In MM patients, stringent CR criteria, in particular the sFLC ratio, do not predict significantly better outcome among MM patients in conventional CR.
We investigated the prognostic impact and clinical utility of serum free light chains (sFLC) and serum heavy-light chains (sHLC) in patients with multiple myeloma treated according to the GEM2005MENOS65, GEM2005MAS65, and GEM2010MAS65 PETHEMA/GEM phase III clinical trials. Serum samples collected at diagnosis were retrospectively analyzed for sFLC (n = 623) and sHLC (n = 183). After induction or autologous transplantation, 309 and 89 samples respectively were available for sFLC and sHLC assays. At diagnosis, a highly abnormal (HA) sFLC ratio (sFLCr) (<0.03 or >32) was not associated with higher risk of progression. After therapy, persistence of involved-sFLC levels >100 mg/L implied worse survival (overall survival [OS], P = 0.03; progression-free survival [PFS], P = 0.007). Among patients that achieved a complete response, sFLCr normalization did not necessarily indicate a higher quality response. We conducted sHLC investigations for IgG and IgA MM. Absolute sHLC values were correlated with monoclonal protein levels measured with serum protein electrophoresis. At diagnosis, HA-sHLCrs (<0.29 or >73) showed a higher risk of progression (P = 0.006). Additionally, involved-sHLC levels >5 g/L after treatment were associated with shorter survival (OS, P = 0.001; PFS, P = 0.018). The HA-sHLCr could have prognostic value at diagnosis; absolute values of involved-sFLC >100 mg/L and involved-sHLC >5 g/L could have prognostic value after treatment.
PurposeMetastatic breast cancer (MBC) progressing after endocrine therapy frequently activates PI3K/AKT/mTOR pathway. The BOLERO-2 trial showed that everolimus-exemestane achieves increased progression free survival (PFS) compared with exemestane. However, there is great inter-patient variability in toxicity and response to exemestane-everolimus treatment. The objective of this study was to perform an exploratory study analyzing the implication of single nucleotide polymorphisms (SNPs) on outcomes from this treatment through a pharmacogenetic analysis.Patients and methodsBlood was collected from 90 postmenopausal women with hormone receptor-positive, HER2-negative MBC treated with exemestane-everolimus following progression after prior treatment with a non-steroidal aromatase inhibitor. Everolimus pharmacokinetics was measured in 37 patients. Twelve SNPs in genes involved in everolimus pharmacokinetics and pharmacodynamics were genotyped and associations assessed with drug plasma levels, clinically relevant toxicities (non-infectious pneumonitis, mucositis, hyperglycemia and hematological toxicities), dose reductions or treatment suspensions due to toxicity, progression free survival (PFS) and overall survival.ResultsWe found that CYP3A4 rs35599367 variant (CYP3A4*22 allele) carriers had higher everolimus blood concentration compared to wild type patients (P = 0.019). ABCB1 rs1045642 was associated with risk of mucositis (P = 0.031), while PIK3R1 rs10515074 and RAPTOR rs9906827 were associated with hyperglycemia and non-infectious pneumonitis (P = 0.016 and 0.024, respectively). Furthermore, RAPTOR rs9906827 was associated with PFS (P = 0.006).ConclusionsCYP3A4*22 allele influenced plasma concentration of everolimus and several SNPs in PI3K/AKT/mTOR pathway genes were associated with treatment toxicities and prognosis. These results require replication, but suggest that germline variation could influence everolimus outcomes in MBC.
, a cumulative total of over 23 million cases of coronavirus disease 2019 (COVID-19) infections and 800,000 related deaths has been reported [1]. Although most infected people present with mild-tomoderate symptoms, about one-third require hospitalization [2] (Last accessed 27 Aug 2020). Identification of valid prognostic factors for patients with COVID-19 might be helpful in the early diagnosis of "high-risk" individuals [3]. Some demographic and clinical variablesnotably age, male sex, smoking or comorbidities such as cardiovascular disease, obesity or diabeteshave been associated with a worse prognosis [4]. By contrast, while some potential blood biomarkers (e.g., lactate dehydrogenase [LDH], C-reactive protein, coagulation parameters or lymphopenia) are emerging [4, 5], the evidence remains scarce and validation using advanced analyses in different cohorts is needed. The use of artificial intelligence (e.g., artificial neural network [ANN]) as a form of predictive analysis could help in this regard, and its combination with standard observation at triage might help to correctly identify those patients at a higher risk [6]. We have studied the prognostic value (in terms of survival) of potential "early" routine biochemistry and hematological biomarkers in patients with COVID-19. This is a retrospective study of all admitted patients diagnosed with COVID-19 (by polymerase chain reaction) in a large public Hospital of Madrid, Spain (Hospital 12 de Octubre) from February 28 to March 30. The protocol was approved by the Ethics Committee of the aforementioned institution (reference #20/222) and adhered to the Declaration of Helsinki. The predictive value (i.e., odds of dying in the hospital versus discharge) of routine serum biochemistry (Cobas 8000 platform; Roche Diagnostics, Risch-Rotkreuz, Switzerland) and hematological parameters (DxH 900 hematology analyzer, Beckman Coulter, Alejandro Santos-Lozano and Fernando Calvo-Boyero contributed equally to this work.
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