The potential impact of CT-MRI matching on tumor volume delineation in advanced head and neck cancer

To study the potential impact of the combined use of CT and MRI scans on the Gross Tumor Volume (GTV) estimation and interobserver variation. Four observers outlined the GTV in six patients with advanced head and neck cancer on CT, axial MRI, and coronal or sagittal MRI. The MRI scans were subsequently matched to the CT scan. The interobserver and interscan set variation were assessed in three dimensions. The mean CT derived volume was a factor of 1.3 larger than the mean axial MRI volume. The range in volumes was larger for the CT than for the axial MRI volumes in five of the six cases. The ratio of the scan set common (i.e., the volume common to all GTVs) and the scan set encompassing volume (i.e., the smallest volume encompassing all GTVs) was closer to one in MRI (0.3-0.6) than in CT (0.1-0.5). The rest volumes (i.e., the volume defined by one observer as GTV in one data set but not in the other data set) were never zero for CT vs. MRI nor for MRI vs. CT. In two cases the craniocaudal border was poorly recognized on the axial MRI but could be delineated with a good agreement between the observers in the coronal/sagittal MRI. MRI-derived GTVs are smaller and have less interobserver variation than CT-derived GTVs. CT and MRI are complementary in delineating the GTV. A coronal or sagittal MRI adds to a better GTV definition in the craniocaudal directio

The impact of loco-regional recurrences on metastatic progression in early-stage breast cancer: a multistate model

To study whether the effects of prognostic factors associated with the occurrence of distant metastases (DM) at primary diagnosis change after the incidence of loco-regional recurrences (LRR) among women treated for invasive stage I or II breast cancer. The study population consisted of 3,601 women, enrolled in EORTC trials 10801, 10854, or 10902 treated for early-stage breast cancer. Data were analysed in a multivariate, multistate model by using multivariate Cox regression models, including a state-dependent covariate. The presence of a LRR in itself is a significant prognostic risk factor (HR: 3.64; 95%-CI: 2.02-6.5) for the occurrence of DM. Main prognostic risk factors for a DM are young age at diagnosis (</=40: HR: 1.79; 95%-CI: 1.28-2.51), larger tumour size (HR: 1.58; 95%-CI: 1.35-1.84) and node positivity (HR: 2.00; 95%-CI: 1.74-2.30). Adjuvant chemotherapy is protective for a DM (HR: 0.66; 95%-CI: 0.55-0.80). After the occurrence of a LRR the latter protective effect has disappeared (P = 0.009). The presence of LRR in itself is a significant risk factor for DM. For patients who are at risk of developing LRR, effective local control should be the main target of therapy

Anal Cancer debuting as Cancer of Unknown Primary

Anal cancer usually presents with a visible or palpable tumour. In this case we describe a 54-year old man diagnosed with Cancer of Unknown Primary (CUP) with a single inguinal node as the only finding. Thorough examination failed to identify any primary tumour. The patient was treated with lymph node dissection and not until nearly two years after initial diagnosis, was the primary tumour found, and the patient was diagnosed with anal cancer. The patient was treated with chemoradiotherapy and 45 months after initial diagnosis there is still no sign of relapse. This case illustrates, that anal cancer can metastasise before the primary tumour is detectable. Furthermore, it demonstrates the necessity of thorough clinical follow-up after treatment of CUP since the primary tumour was found later. Finally this is a case of a long-term survivor following treatment for metastatic inguinal lymph nodes from an initially unknown primary cancer

Normal tissue complication probability (NTCP) parameters for breast fibrosis: pooled results from two randomised trials

Introduction: the dose–volume effect of radiation therapy on breast tissue is poorly understood. We estimate NTCP parameters for breast fibrosis after external beam radiotherapy.Materials and methods: we pooled individual patient data of 5856 patients from 2 trials including whole breast irradiation followed with or without a boost. A two-compartment dose volume histogram model was used with boost volume as the first compartment and the remaining breast volume as second compartment. Results from START-pilot trial (n?=?1410) were used to test the predicted models.Results: 26.8% patients in the Cambridge trial (5?years) and 20.7% patients in the EORTC trial (10?years) developed moderate-severe breast fibrosis. The best fit NTCP parameters were BEUD3(50)?=?136.4?Gy, ?50?=?0.9 and n?=?0.011 for the Niemierko model and BEUD3(50)?=?132?Gy, m?=?0.35 and n?=?0.012 for the Lyman Kutcher Burman model. The observed rates of fibrosis in the START-pilot trial agreed well with the predicted rates.Conclusions: this large multi-centre pooled study suggests that the effect of volume parameter is small and the maximum RT dose is the most important parameter to influence breast fibrosis. A small value of volume parameter ‘n’ does not fit with the hypothesis that breast tissue is a parallel organ. However, this may reflect limitations in our current scoring system of fibrosi

Differential expression of proinflammatory cytokines and their inhibitors during the course of meningococcal infections

Contains fulltext : 4764.pdf (publisher's version ) (Open Access

Elevated acute phase proteins affect pharmacokinetics in COVID-19 trials: Lessons from the CounterCOVID - imatinib study.

This study aimed to determine whether published pharmacokinetic (PK) models can adequately predict the PK profile of imatinib in a new indication, such as coronavirus disease 2019 (COVID-19). Total (bound + unbound) and unbound imatinib plasma concentrations obtained from 134 patients with COVID-19 participating in the CounterCovid study and from an historical dataset of 20 patients with gastrointestinal stromal tumor (GIST) and 85 patients with chronic myeloid leukemia (CML) were compared. Total imatinib area under the concentration time curve (AUC), maximum concentration (C &lt;sub&gt;max&lt;/sub&gt; ) and trough concentration (C &lt;sub&gt;trough&lt;/sub&gt; ) were 2.32-fold (95% confidence interval [CI] 1.34-3.29), 2.31-fold (95% CI 1.33-3.29), and 2.32-fold (95% CI 1.11-3.53) lower, respectively, for patients with CML/GIST compared with patients with COVID-19, whereas unbound concentrations were comparable among groups. Inclusion of alpha1-acid glycoprotein (AAG) concentrations measured in patients with COVID-19 into a previously published model developed to predict free imatinib concentrations in patients with GIST using total imatinib and plasma AAG concentration measurements (AAG-PK-Model) gave an estimated mean (SD) prediction error (PE) of -20% (31%) for total and -7.0% (56%) for unbound concentrations. Further covariate modeling with this combined dataset showed that in addition to AAG; age, bodyweight, albumin, CRP, and intensive care unit admission were predictive of total imatinib oral clearance. In conclusion, high total and unaltered unbound concentrations of imatinib in COVID-19 compared to CML/GIST were a result of variability in acute phase proteins. This is a textbook example of how failure to take into account differences in plasma protein binding and the unbound fraction when interpreting PK of highly protein bound drugs, such as imatinib, could lead to selection of a dose with suboptimal efficacy in patients with COVID-19