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Iskalni niz: "ključne besede" (treatment outcome) .

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1.
Treatment outcomes and relative dose intensity of chemotherapy in patients with advanced Hodgkin lymphoma
Samo Rožman, Barbara Jezeršek Novaković, Nina Ružić Gorenjec, Srdjan Novaković, 2022, izvirni znanstveni članek

Povzetek: The present retrospective study was undertaken to investigate the association of relative dose intensity (RDI) with the outcome of patients with advanced stage Hodgkin lymphoma (HL) receiving ABVD (doxorubicin, bleomycin, vinblastine, dacarbazine) and escalated BEACOPP regimens (bleomycin, etoposide, doxorubicin, cyclophosphamide, vincristine, procarbazine, prednisone). A total of 114 patients with HL treated between 2004 and 2013 were enrolled for evaluation. The association of variables with overall survival (OS) and progression-free survival (PFS) was analysed using univariate and multivariate Cox proportional hazards models. The median age of patients was 39 years, and the majority were male and had stage IV disease. A total of 54 patients received ABVD and 60 received BEACOPP chemotherapy with 24 and four deaths, respectively. Patients in the BEACOPP group were significantly younger with lower Charlson comorbidity index (CCI) and better performance status in comparison with the ABVD group, making the comparison of groups not possible. In the ABVD group, RDI was not significantly associated with OS (P=0.590) or PFS (P=0.354) in a multivariate model where age was controlled. The low number of events prevented this analysis in the BEACOPP group. The age of patients was strongly associated with both OS and PFS; all statistically significant predictors for OS and PFS from univariate analyses (chemotherapy regimen, CCI, RDI, performance status) lost their effect in multivariate analyses where age was controlled. Based on these observations, it was concluded that RDI was not associated with OS or PFS after age is controlled, neither in all patients combined nor in the ABVD group.
Ključne besede: Hodgkin lymphoma, chemotherapy, outcome, primary treatment
Objavljeno v DiRROS: 23.09.2022; Ogledov: 520; Prenosov: 159
.pdf Celotno besedilo (794,55 KB)

2.
Treatment outcome clustering patterns correspond to discrete asthma phenotypes in children
Ivana Banić, Mario Lovrić, Gerald Cuder, Roman Kern, Matija Rijavec, Peter Korošec, Mirjana Kljajić-Turkalj, 2021, izvirni znanstveni članek

Povzetek: Despite widely and regularly used therapy asthma in children is not fully controlled. Recognizing the complexity of asthma phenotypes and endotypes imposed the concept of precision medicine in asthma treatment. By applying machine learning algorithms assessed with respect to their accuracy in predicting treatment outcome, we have successfully identified 4 distinct clusters in a pediatric asthma cohort with specific treatment outcome patterns according to changes in lung function (FEV1 and MEF50), airway inflammation (FENO) and disease control likely affected by discrete phenotypes at initial disease presentation, differing in the type and level of inflammation, age of onset, comorbidities, certain genetic and other physiologic traits. The smallest and the largest of the 4 clusters- 1 (N = 58) and 3 (N = 138) had better treatment outcomes compared to clusters 2 and 4 and were characterized by more prominent atopic markers and a predominant allelic (A allele) effect for rs37973 in the GLCCI1 gene previously associated with positive treatment outcomes in asthmatics. These patients also had a relatively later onset of disease (6 + yrs). Clusters 2 (N = 87) and 4 (N = 64) had poorer treatment success, but varied in the type of inflammation (predominantly neutrophilic for cluster 4 and likely mixed-type for cluster 2), comorbidities (obesity for cluster 2), level of systemic inflammation (highest hsCRP for cluster 2) and platelet count (lowest for cluster 4). The results of this study emphasize the issues in asthma management due to the overgeneralized approach to the disease, not taking into account specific disease phenotypes.
Ključne besede: asthma, allergy and immunology, pediatrics, machine learning, treatment outcome, phenotypes, childhood asthma, clustering
Objavljeno v DiRROS: 16.08.2021; Ogledov: 912; Prenosov: 643
.pdf Celotno besedilo (1,32 MB)
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