An overall strategy based on regression models to estimate relative survival and model the effects of prognostic factors in cancer survival studies.

Relative survival provides a measure of the proportion of patients dying from the disease under study without requiring the knowledge of the cause of death. We propose an overall strategy based on regression models to estimate the relative survival and model the effects of potential prognostic factors. The baseline hazard was modelled until 10 years follow-up using parametric continuous functions. Six models including cubic regression splines were considered and the Akaike Information Criterion was used to select the final model. This approach yielded smooth and reliable estimates of mortality hazard and allowed us to deal with sparse data taking into account all the available information. Splines were also used to model simultaneously non-linear effects of continuous covariates and time-dependent hazard ratios. This led to a graphical representation of the hazard ratio that can be useful for clinical interpretation. Estimates of these models were obtained by likelihood maximization. We showed that these estimates could be also obtained using standard algorithms for Poisson regression

Performance of two formal tests based on martingales residuals to check the proportional hazard assumption and the functional form of the prognostic factors in flexible parametric excess hazard models.

: Net survival, the one that would be observed if the disease under study was the only cause of death, is an important, useful, and increasingly used indicator in public health, especially in population-based studies. Estimates of net survival and effects of prognostic factor can be obtained by excess hazard regression modeling. Whereas various diagnostic tools were developed for overall survival analysis, few methods are available to check the assumptions of excess hazard models. We propose here two formal tests to check the proportional hazard assumption and the validity of the functional form of the covariate effects in the context of flexible parametric excess hazard modeling. These tests were adapted from martingale residual-based tests for parametric modeling of overall survival to allow adding to the model a necessary element for net survival analysis: the population mortality hazard. We studied the size and the power of these tests through an extensive simulation study based on complex but realistic data. The new tests showed sizes close to the nominal values and satisfactory powers. The power of the proportionality test was similar or greater than that of other tests already available in the field of net survival. We illustrate the use of these tests with real data from French cancer registries.<br/

Radiation-induced decomposition of the metal-organic molecule Bis(4-cyano-2,2,6,6-tetramethyl-3,5-heptanedionato)copper(II)

The effects of vacuum ultraviolet radiation on the adsorbed copper center molecule bis(4-cyano-2,2,6,6- tetramethyl-3,5-heptanedionato)copper(II) (or Cu(CNdpm)2), (C24H36N2O4Cu, Cu(II)) was studied by photoemission spectroscopy. Changes in the ultraviolet photoemission spectra (UPS) of Cu(CNdpm)2, adsorbed on Co(1 1 1), indicate that the ultraviolet radiation leads to decomposition of Cu(CNdpm)2 and this decomposition is initially dominated by loss of peripheral hydrogen

Radiation-induced decomposition of the metal-organic molecule Bis(4-cyano-2,2,6,6-tetramethyl-3,5-heptanedionato)copper(II)

The effects of vacuum ultraviolet radiation on the adsorbed copper center molecule bis(4-cyano-2,2,6,6- tetramethyl-3,5-heptanedionato)copper(II) (or Cu(CNdpm)2), (C24H36N2O4Cu, Cu(II)) was studied by photoemission spectroscopy. Changes in the ultraviolet photoemission spectra (UPS) of Cu(CNdpm)2, adsorbed on Co(1 1 1), indicate that the ultraviolet radiation leads to decomposition of Cu(CNdpm)2 and this decomposition is initially dominated by loss of peripheral hydrogen

Immunomodulatory Therapy for MIS-C.

Studies comparing initial therapy for multisystem inflammatory syndrome in children (MIS-C) provided conflicting results. To compare outcomes in MIS-C patients treated with intravenous immunoglobulin (IVIG), glucocorticoids, or the combination thereof. Medline, Embase, CENTRAL and WOS, from January 2020 to February 2022. Randomized or observational comparative studies including MIS-C patients &lt;21 years. Two reviewers independently selected studies and obtained individual participant data. The main outcome was cardiovascular dysfunction (CD), defined as left ventricular ejection fraction &lt; 55% or vasopressor requirement ≥ day 2 of initial therapy, analyzed with a propensity score-matched analysis. Of 2635 studies identified, 3 nonrandomized cohorts were included. The meta-analysis included 958 children. IVIG plus glucocorticoids group as compared with IVIG alone had improved CD (odds ratio [OR] 0.62 [0.42-0.91]). Glucocorticoids alone group as compared with IVIG alone did not have improved CD (OR 0.57 [0.31-1.05]). Glucocorticoids alone group as compared with IVIG plus glucocorticoids did not have improved CD (OR 0.67 [0.24-1.86]). Secondary analyses found better outcomes associated with IVIG plus glucocorticoids compared with glucocorticoids alone (fever ≥ day 2, need for secondary therapies) and better outcomes associated with glucocorticoids alone compared with IVIG alone (left ventricular ejection fraction &lt; 55% ≥ day 2). Nonrandomized nature of included studies. In a meta-analysis of MIS-C patients, IVIG plus glucocorticoids was associated with improved CD compared with IVIG alone. Glucocorticoids alone was not associated with improved CD compared with IVIG alone or IVIG plus glucocorticoids

Major depression and survival in people with cancer

OBJECTIVE: The question of whether depression is associated with worse survival in people with cancer remains unanswered because of methodological criticism of the published research on the topic. We aimed to study the association in a large methodologically robust study. METHODS: We analysed data on 20,582 patients with breast, colorectal, gynaecological, lung and prostate cancers who had attended cancer outpatient clinics in Scotland, UK. Patients had completed two-stage screening for major depression as part of their cancer care. These data on depression status were linked to demographic, cancer and subsequent mortality data from national databases. We estimated the association of major depression with survival for each cancer using Cox regression. We adjusted for potential confounders and interactions between potentially time-varying confounders and the interval between cancer diagnosis and depression screening, and used multiple imputation for missing depression and confounder data. We pooled the cancer-specific results using fixed-effects meta-analysis. RESULTS: Major depression was associated with worse survival for all cancers, with similar adjusted hazard ratios: breast cancer (HR 1.42, 95% CI 1.15-1.75), colorectal cancer (HR 1.47, 95% CI 1.11-1.94), gynaecological cancer (HR 1.36, 95% CI 1.08-1.71), lung cancer (HR 1.39, 95% CI 1.24-1.56), prostate cancer (HR 1.76, 95% CI 1.08-2.85). The pooled hazard ratio was 1.41 (95% CI 1.29-1.54, p<0.001, I2=0%). These findings were not materially different when we only considered the deaths (90%) that were attributed to cancer. CONCLUSIONS: Major depression is associated with worse survival in patients with common cancers. The mechanisms of this association and the clinical implications require further study

MAJOR DEPRESSION AND SURVIVAL IN PEOPLE WITH CANCER

OBJECTIVE: The question of whether depression is associated with worse survival in people with cancer remains unanswered because of methodological criticism of the published research on the topic. We aimed to study the association in a large methodologically robust study. METHODS: We analyzed data on 20,582 patients with breast, colorectal, gynecological, lung, and prostate cancers who had attended cancer outpatient clinics in Scotland, United Kingdom. Patients had completed two-stage screening for major depression as part of their cancer care. These data on depression status were linked to demographic, cancer, and subsequent mortality data from national databases. We estimated the association of major depression with survival for each cancer using Cox regression. We adjusted for potential confounders and interactions between potentially time-varying confounders and the interval between cancer diagnosis and depression screening, and used multiple imputation for missing depression and confounder data. We pooled the cancer-specific results using fixed-effects meta-analysis. RESULTS: Major depression was associated with worse survival for all cancers, with similar adjusted hazard ratios (HRs): breast cancer (HR = 1.42, 95% confidence interval [CI] = 1.15-1.75), colorectal cancer (HR = 1.47, 95% CI = 1.11-1.94), gynecological cancer (HR = 1.36, 95% CI = 1.08-1.71), lung cancer (HR = 1.39, 95% CI = 1.24-1.56), and prostate cancer (HR = 1.76, 95% CI = 1.08-2.85). The pooled HR was 1.41 (95% CI = 1.29-1.54, p < .001, I2 = 0%). These findings were not materially different when we only considered the deaths (90%) that were attributed to cancer. CONCLUSIONS: Major depression is associated with worse survival in patients with common cancers. The mechanisms of this association and the clinical implications require further study