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Abstract In the frontline high-dose phase 3 FIL-MCL0208 trial (NCT02354313), 8% of enrolled mantle cell lymphoma (MCL) patients could not be randomised to receive lenalidomide (LEN) maintenance vs observation after autologous stem cell transplantation (ASCT) due to inadequate hematological recovery and 52% of those who started LEN, needed a dose reduction due to toxicity. We therefore focused on the role played by CD34 + hematopoietic stem cells (PBSC) harvesting and reinfusion on toxicity and outcome. Overall, 90% (n = 245) of enrolled patients who underwent the first leukapheresis collected ≥ 4 × 106 PBSC/kg, 2.6% (n = 7) mobilized 10 days) was associated with a worse outcome, both in terms of PFS and OS. In conclusion, although the harvesting procedures proved feasible for younger MCL patients, long-lasting cytopenia following ASCT remains a significant issue: this can hinder the administration of effective maintenance therapies, potentially increasing the relapse rate and negatively affecting survival outcomes.

Abstract Background Conservative management is recommended as the first therapeutic step in chronic low back pain (LBP), but there is no available evidence regarding the possible effect of patients’ baseline characteristics on the therapeutic outcomes. A systematic review of the literature was performed to investigate this point. Methods In February 2024, all the level I studies investigating the role of pharmacological management for chronic LBP were accessed. Data concerning the patient demographic at baseline were collected: number of patients and related mean BMI and age, duration of the symptoms, duration of the follow-up, percentage of females, Numeric Rating Scale (NRS), the Roland Morris Disability Questionnaire (RMQ), Oswestry Disability Index (ODI). The outcomes at the last follow-up were evaluated through NRS, RMQ, and ODI. A multiple linear model regression diagnostic through the Pearson Product-Moment Correlation Coefficient (r) was used. Results Data from 47 articles (9007 patients) were obtained. The analysis yielded the following significant associations: age at baseline and NRS at follow-up (r = − 0.22; P = 0.04), NRS at baseline with NRS (r = 0.26; P = 0.03) and RMQ (r = − 0.58; P = 0.02) at follow-up, RMQ at baseline and the same at follow-up (r = 0.69; P = 0.0001). Conclusion Older age, higher BMI, presence of comorbidities, higher ODI and a long history of symptoms or surgical treatments do not reduce the efficacy of pharmacological management of chronic LBP. However, pharmacological therapy is not an effective option for patients with high baseline RMQ. Level of evidence I systematic review of RCTs.

Triage systems, calibrated to discriminate acute conditions, seem unable to deal with minor non-urgent conditions. The aim of the present study to verify whether some level 4 priority codes can be safely declassified to level 5 priority codes. A prospective observational study was performed between 1° October 2022 to 31° March 2023. All patients with a code 5 according to the Manchester Triage System (MTS) were compared with patients with a priority level 4 code but with a general indicator that was downgraded to a code 5 after the triage nurse's assessment. Of the 2032 patients enrolled, 58.6% were part of the 'blue from MTS' group while 41.4% were part of the 'blue after re-evaluation' group. There was no statistical difference in the rate of hospitalisation and discharge between the two groups (p=0.928). There was also no difference between the two groups in the comparisons of short- and medium-term death. This study highlights the need to rethink strategies to declassify patients through MTS, especially given the continuous increase of non-urgent patients presenting in the ED.

IntroductionThe increasing survival of patients with breast cancer has prompted the assessment of mortality due to all causes of death in these patients. We estimated the absolute risks of death from different causes, useful for health-care planning and clinical prediction, as well as cause-specific hazards, useful for hypothesis generation on etiology and risk factors.Materials and methodsUsing data from population-based cancer registries we performed a retrospective study on a cohort of women diagnosed with primary breast cancer. We carried out a competing-cause analysis computing cumulative incidence functions (CIFs) and cause-specific hazards (CSHs) in the whole cohort, separately by age, stage and registry area.ResultsThe study cohort comprised 12,742 women followed up for six years. Breast cancer showed the highest CIF, 13.71%, and cardiovascular disease was the second leading cause of death with a CIF of 3.60%. The contribution of breast cancer deaths to the CIF for all causes varied widely by age class: 89.25% in women diagnosed at age

For patients with sepsis in the Emergency Department (ED), early risk stratification is important to improve prognosis. The study aimed to evaluate the predictive role of estimated plasma volume (ePVS) on admission to the ED. All sepsis patients who were admitted to our ED in 2021, were included in this prospective study. Multivariate models adjusted for patients' clinical characteristics were used to assess the contribution of ePVS to the independent prediction of death at 30 days. A total of 455 septic patients were enrolled and 16.9% of patients died. Patients who survived to 30 days had a mean ePVS of 5.19, while those who died at 30 days had a value of 5.74 (p=0.004). ePVS was an independent risk factor for 30-day mortality with an adjusted OR of 1.211 (95% CI 1.004–1.460, p=0.045). The AUROC of ePVS was 0.619 (95% CI 0.545–0.689). Decision tree analysis showed a predictive role for ePVS in less severe patients. In septic patients, ePVS is an independent predictor of 30-day mortality and may improve risk prediction in less severe patients.

Introduction: The excellent soft-tissue contrast of magnetic resonance imaging (MRI) is appealing for delineation of organs-at-risk (OARs) as it is required for radiation therapy planning (RTP). In the last decade there has been an increasing interest in using deep-learning (DL) techniques to shorten the labor-intensive manual work and increase reproducibility. This paper focuses on the automatic segmentation of 27 head-and-neck and 10 male pelvis OARs with deep-learning methods based on T2-weighted MR images.Method: The proposed method uses 2D U-Nets for localization and 3D U-Net for segmentation of the various structures. The models were trained using public and private datasets and evaluated on private datasets only.Results and discussion: Evaluation with ground-truth contours demonstrated that the proposed method can accurately segment the majority of OARs and indicated similar or superior performance to state-of-the-art models. Furthermore, the auto-contours were visually rated by clinicians using Likert score and on average, 81% of them was found clinically acceptable.

IntroductionVariation in stage at diagnosis of childhood cancers (CC) may explain differences in survival rates observed across geographical regions. The BENCHISTA project aims to understand these differences and to encourage the application of the Toronto Staging Guidelines (TG) by Population-Based Cancer Registries (PBCRs) to the most common solid paediatric cancers.MethodsPBCRs within and outside Europe were invited to participate and identify all cases of Neuroblastoma, Wilms Tumour, Medulloblastoma, Ewing Sarcoma, Rhabdomyosarcoma and Osteosarcoma diagnosed in a consecutive three-year period (2014-2017) and apply TG at diagnosis. Other non-stage prognostic factors, treatment, progression/recurrence, and cause of death information were collected as optional variables. A minimum of three-year follow-up was required. To standardise TG application by PBCRs, on-line workshops led by six tumour-specific clinical experts were held. To understand the role of data availability and quality, a survey focused on data collection/sharing processes and a quality assurance exercise were generated. To support data harmonization and query resolution a dedicated email and a question-and-answers bank were created.Results67 PBCRs from 28 countries participated and provided a maximally de-personalized, patient-level dataset. For 26 PBCRs, data format and ethical approval obtained by the two sponsoring institutions (UCL and INT) was sufficient for data sharing. 41 participating PBCRs required a Data Transfer Agreement (DTA) to comply with data protection regulations. Due to heterogeneity found in legal aspects, 18 months were spent on finalizing the DTA. The data collection survey was answered by 68 respondents from 63 PBCRs; 44% of them confirmed the ability to re-consult a clinician in cases where stage ascertainment was difficult/uncertain. Of the total participating PBCRs, 75% completed the staging quality assurance exercise, with a median correct answer proportion of 92% [range: 70% (rhabdomyosarcoma) to 100% (Wilms tumour)].ConclusionDifferences in interpretation and processes required to harmonize general data protection regulations across countries were encountered causing delays in data transfer. Despite challenges, the BENCHISTA Project has established a large collaboration between PBCRs and clinicians to collect detailed and standardised TG at a population-level enhancing the understanding of the reasons for variation in overall survival rates for CC, stimulate research and improve national/regional child health plans.

ObjectivesTo describe the procedures to derive complete prevalence and several indicators of cancer cure from population-based cancer registries.Materials and methodsCancer registry data (47% of the Italian population) were used to calculate limited duration prevalence for 62 cancer types by sex and registry. The incidence and survival models, needed to calculate the completeness index (R) and complete prevalence, were evaluated by likelihood ratio tests and by visual comparison. A sensitivity analysis was conducted to explore the effect on the complete prevalence of using different R indexes. Mixture cure models were used to estimate net survival (NS); life expectancy of fatal (LEF) cases; cure fraction (CF); time to cure (TTC); cure prevalence, prevalent patients who were not at risk of dying as a result of cancer; and already cured patients, those living longer than TTC at a specific point in time. CF was also compared with long-term NS since, for patients diagnosed after a certain age, CF (representing asymptotical values of NS) is reached far beyond the patient’s life expectancy.ResultsFor the most frequent cancer types, the Weibull survival model stratified by sex and age showed a very good fit with observed survival. For men diagnosed with any cancer type at age 65–74 years, CF was 41%, while the NS was 49% until age 100 and 50% until age 90. In women, similar differences emerged for patients with any cancer type or with breast cancer. Among patients alive in 2018 with colorectal cancer at age 55–64 years, 48% were already cured (had reached their specific TTC), while the cure prevalence (lifelong probability to be cured from cancer) was 89%. Cure prevalence became 97.5% (2.5% will die because of their neoplasm) for patients alive >5 years after diagnosis.ConclusionsThis study represents an addition to the current knowledge on the topic providing a detailed description of available indicators of prevalence and cancer cure, highlighting the links among them, and illustrating their interpretation. Indicators may be relevant for patients and clinical practice; they are unambiguously defined, measurable, and reproducible in different countries where population-based cancer registries are active.

ObjectivesWe aimed to (1) describe the course of the emotional burden (i.e., depression, anxiety, and stress) in a general population sample during the coronavirus pandemic in 2020 and 2021 and (2) explore the association between emotional burden and a serologically proven infection with SARS-CoV-2.Study designThis longitudinal study involved a sample of community-dwelling persons aged ≥14 years from the general population of South Tyrol (Province of Bolzano-Bozen, Northern Italy). Data were collected at two stages over a 1-year period in 2020 and 2021.MethodsPersons were invited to participate in a survey on socio-demographic, health-related and psychosocial variables (e.g., age, chronic diseases, Depression Anxiety Stress Scale, DASS-21), as well as in the serological testing for of SARS-CoV-2-specific immunoglobulins.ResultsIn 2020, 855 (23.8%) out of 3,600 persons participated; in 2021, 305 (35.7%) out of 855 were tested again. We observed a statistically significant decrease in mean DASS-21 scores for depression, stress, and total scores between 2020 and 2021, yet not for anxiety. Persons with a confirmed SARS-CoV-2-infection between the first and second data collection exhibited increased emotional burden compared to those without SARS-CoV-2-infection. The odds of participants with a self-reported diagnosis of mental disorder for future infection with SARS-CoV-2 was almost four times higher than that of participants without mental disorders (OR:3.75; 95%CI:1.79-7.83).ConclusionOur findings support to the hypothesis of a psycho-neuroendocrine-immune interplay in COVID-19. Further research is necessary to explore the mechanisms underlying the interplay between mental health and SARS-CoV-2 infections.