Monoclonal gammopathies (MGs) are a wide range of diseases that may evolve or progress over time. Comorbidity plays a critical role in this setting. The co-occurrence of two MGs is not a rare event. The evidence on the association of systemic light chain (AL) amyloidosis and multiple myeloma (MM) is scarce and controversial. Herein we aim to address this topic in a large series of patients of a referral center. All consecutive AL amyloidosis patients treated at our center from January 2005 to April 2023 were prospectively enrolled in a clinical and epidemiological registry. 141 patients diagnosed with AL amyloidosis were included, of which 7 (5%) had localized whereas 134 presented with systemic disease. The heart was the most frequently affected organ (90.3%). 25 patients (18.7%) fulfilled the IMWG diagnostic criteria of MM (AL/MM). Time-dependent association between AL and MM showed that the synchronous pattern is more frequent than the appearance of a second primary malignancy. The diagnostic delay was six months (m). Patients with AL/MM had a poorer median overall survival (OS) than AL-only patients (35.5 m, CI 95% 0–88.9, vs. 52.6 m, CI 95% 16.7–88.5), but this difference was not statistically significant. The prognosis in AL is dominated by the heart involvement, which is massive in this series. In our Cox regression model, only three prognostic variables remain as independent prognostic factors: age, N-terminal pro-brain natriuretic peptide (≥8500 ng/L), and undergoing an autologous stem cell transplant, whereas left ventricular ejection fraction shows a marginal effect. More and large studies focusing on the AL/MM association are needed to uncover the characteristics and prognostic impact of this association.

Background/Objectives: Neutropenia is a frequent complication among solid organ transplant (SOT) recipients receiving immunosuppressive therapy and antimicrobial prophylaxis. However, there are limited studies analysing the frequency and impact of neutropenia in lung transplant recipients (LTRs). Our aim was to analyse the frequency of neutropenia, the need for granulocyte colony-stimulating factor (GCSF) treatment within the first 18 months post-transplant and its association with acute rejection, chronic lung allograft dysfunction (CLAD), overall survival and the development of infections. Methods: This observational and retrospective study recruited 305 patients who underwent lung transplantation between 2009 and 2019, with outpatient quarterly follow-up during the first 18 months post-surgery.Results: During this period, 51.8% of patients experienced at least one episode of neutropenia. Neutropenia was classified as mild in 50.57% of cases, moderate in 36.88% and severe in 12.54%. GCSF treatment was indicated in 23.28% of patients, with a mean dose of 3.53 units. No statistically significant association was observed between neutropenia or its severity and the development of acute rejection, CLAD or overall survival. However, the patients who received GCSF treatment had a higher mortality rate compared to those who did not. Sixteen patients (5.25%) developed infections during neutropenia, with bacterial infections being the most common. Conclusions: Neutropenia is common in the first 18 months after lung transplantation and most episodes are mild. We did not find an association between neutropenia and acute rejection, CLAD, or mortality. However, the use of GCSF were associated with worse post-transplant survival.

Background: The growing complexity and cost of oncohematological treatments has created an urgent need for standardized methodologies capable of enabling inter-institutional comparisons of healthcare expenditure within homogeneous patient groups. Cancer-related pharmaceutical costs vary substantially depending on tumour type, disease stage, and therapeutic approach, making cross-institutional benchmarking challenging due to heterogeneity in patient populations and clinical practice patterns. Therefore, integrating cost analysis with clinically meaningful patient stratification is essential to improve resource allocation and outcome evaluation. Methods: A multicentre working group comprising four tertiary hospitals in Madrid (Spain) was established to develop and preliminarily evaluate a novel classification system for adult oncohematological patients. A standardized methodology was designed to stratify patients into homogeneous groups (PATONCO categories) based on tumor location, therapeutic objective, and clinically relevant biomarkers. A cost indicator was defined as the average cost per patient per month for each PATONCO category. Data were extracted from pharmacy dispensing systems and analyzed using descriptive and inferential statistics, including Kruskal–Wallis and post hoc Dunn tests. Results: A total of 3659 patients were included (3168 oncology; 491 hematology), distributed across 62 programmes (54 oncology; 8 hematology). The PATONCOS tool enabled the identification and validation of a cost indicator (average cost/patient/month per category), allowing inter-hospital comparison. Significant differences in costs were observed across most high-prevalence categories, reflecting variability in drug selection within homogeneous patient groups, as documented by the differential use of specific therapeutic agents across centers. The model demonstrated its capacity to detect intra-group homogeneity and inter-group variability, improving the identification of high-cost patient subgroups and supporting benchmarking across centers. Conclusions: The PATONCOS tool provides a novel, clinically oriented stratification methodology that integrates pharmacotherapy, biomarkers, and disease stage with economic evaluation. This approach enables more accurate comparisons of oncology treatment costs between institutions and may support data-driven decision-making in resource allocation. Its implementation may contribute to more sustainable healthcare systems by aligning clinical practice with economic outcomes.

Background/Objectives: Cytomegalovirus (CMV) infection is a frequent complication after lung transplantation, especially in high-risk donor-positive/recipient-negative (D+/R−) patients. CMV-specific hyperimmunoglobulin (CMV-HIG), administered either with antivirals or as monotherapy, may be beneficial for preventing or treating CMV infection in selected clinical scenarios. This study evaluated CMV-HIG indications and their impact on clinical outcomes in our lung transplant unit. Methods: We retrospectively analyzed adult lung transplant recipients (2010–2023) who received ≥2 doses of CMV-HIG for universal prophylaxis, monotherapy prophylaxis, preemptive therapy, or treatment of invasive disease. Results: CMV-HIG was administered to 204 out of 336 recipients (61%). CMV-HIG was well tolerated, with no treatment-related adverse events. Indications were preemptive therapy (63%), universal prophylaxis (24%), monotherapy prophylaxis (7%), and treatment of invasive disease (6%). CMV-HIG was well tolerated, with no treatment-related adverse events. No patients developed invasive disease during combination prophylaxis or preemptive treatment. The combination treatment of patients with invasive disease was also effective, and no cases of VGC resistance were detected. CMV-HIG monoprophylaxis has allowed us to delay or prevent viral replication in recipients who developed VGC side effects. Rates of acute rejection, Chronic Lung Allograft Dysfunction (CLAD), and overall survival were similar across CMV risk groups. Conclusions: Our results showed that the combined use of CMV-HIG and antiviral agents is effective in preventing CMV infection and disease in high-risk lung transplant recipients. This combination is also useful in treating invasive disease and preventing VGC resistance. Additionally, CMV-HIG monoprohylaxis can delay or prevent viral replication in recipients experiencing VGC-related side effects. These findings support the use of CMV-HIG in selected clinical settings, although prospective studies are needed to define its potential benefits within the current therapeutic armamentarium.

Background:Advances in oncology have led to the development of novel targeted therapies with demonstrated efficacy in clinical trials; however, their real-world economic impact prior to and after market introduction remains insufficiently characterized [1,2]. Cancer-related healthcare costs vary significantly depending on disease stage, time since diagnosis, tumor type, and therapeutic approach[3–6], making inter-hospital comparisons challenging due to heterogeneity in patient populations and information systems [7]. Therefore, integrating cost analysis with clinically meaningful patient stratification is essential to improve resource allocation and outcome evaluation[8–12]. Methods: A multicentre working group comprising four tertiary hospitals in Madrid (Spain) was established to develop and validate a novel classification system for adult oncohematological patients. A standardized methodology was designed to stratify patients into homogeneous groups (PATONCO categories) based on tumor location, therapeutic objective, and clinically relevant biomarkers. A cost indicator was defined as the average cost per patient per month for each PATONCO category. Data were extracted from pharmacy dispensing systems and analyzed using descriptive and inferential statistics, including Kruskal–Wallis and post hoc Dunn tests. Results: A total of 3,659 patients were included (3,168 oncology; 491 hematology), distributed across 62 programmes (54 oncology; 8 hematology). The PATONCOS tool enabled the identification and validation of a cost indicator (average cost/patient/month per category), allowing inter-hospital comparison. Significant differences in costs were observed across most high-prevalence categories, reflecting variability in therapeutic strategies and adoption of innovative treatments. The model demonstrated its capacity to detect intra-group homogeneity and inter-group variability, improving the identification of high-cost patient subgroups and supporting benchmarking across centres. Conclusions: The PATONCOS tool provides a novel, clinically oriented stratification methodology that integrates pharmacotherapy, biomarkers, and disease stage with economic evaluation. This approach enables more accurate comparisons of oncology treatment costs between institutions and supports data-driven decision-making in resource allocation. Its implementation may contribute to more sustainable healthcare systems by aligning clinical practice with economic outcomes.