Brain-derived neurotrophic factor as a biomarker in cancer-related cognitive impairment among adolescent and young adult cancer patients.

Brain-derived neurotrophic factor (BDNF) improves cognitive function by stimulating neurogenesis and neuroplasticity. We hypothesize that higher plasma BDNF levels are protective against cognitive toxicity among adolescent and young adult cancer patients (15-39 years old). In a prospective, longitudinal study, we recruited 74 newly diagnosed cancer and 118 age-matched non-cancer controls who completed the Cambridge Neuropsychological Test Automated Battery (CANTAB), Functional Assessment of Cancer Therapy-Cognitive Function questionnaire (FACT-Cog) and blood draws. Plasma BDNF was quantified using an enzyme-linked immunosorbent assay. Genomic DNA from buffy coat was genotyped for BDNF Val66Met. Most cancer participants were diagnosed with breast (24%) and head/neck (22%) cancers. After adjusting for sociodemographic variables (age, gender, race, marital status, education years), cancer participants had lower BDNF levels (ng/mL) at baseline (median: 10.7 vs 21.6, p < 0.001) and 6-months post-baseline (median: 8.2 vs 15.3, p = 0.001) compared to non-cancer controls. Through linear mixed modelling adjusted for sociodemographic variables, baseline cognition, fatigue, psychological distress, and time, we observed that among cancer participants, lower baseline BDNF levels were associated with worse attention (p = 0.029), memory (p = 0.018) and self-perceived cognitive abilities (p = 0.020) during cancer treatment. Met/Met was associated with enhanced executive function compared to Val/Val (p = 0.012). Plasma BDNF may serve as a predictive biomarker of cancer-related cognitive impairment.

Post-Treatment Neutrophil and Lymphocyte Counts Predict Progression-Free Survival Following First-Line Chemotherapy in Hodgkin's Lymphoma.

Hodgkin's lymphoma carries an excellent prognosis with modern chemotherapy, but a significant proportion of patients remain refractory to or relapse after first-line treatment. Immunological changes post-treatment, such as chemotherapy-induced neutropenia (CIN) or lymphopenia, have shown prognostic significance in multiple tumor types. Our study aims to investigate the prognostic value of immunologic changes in Hodgkin's lymphoma by examining the post-treatment lymphocyte count (pALC), neutrophil count (pANC) and the neutrophil-lymphocyte ratio (pNLR). Patients treated for classical Hodgkin's lymphoma at the National Cancer Centre Singapore using ABVD-based regimens were retrospectively analyzed. An optimal cut-off value for high pANC, low pALC and high pNLR in predicting progression-free survival was determined by receiver operating curve analysis. Survival analysis was performed using the Kaplan-Meier method and multivariable Cox proportional models. Overall OS and PFS were excellent, with a 5-year OS of 99.2% and a 5-year PFS of 88.2%. Poorer PFS was associated with high pANC (HR 2.99, p = 0.0392), low pALC (HR 3.95, p = 0.0038) and high pNLR (p = 0.0078). In conclusion, high pANC, low pALC and high pNLR confer a poorer prognosis for Hodgkin's lymphoma. Future studies should evaluate the potential of improving treatment outcomes by the adjustment of chemotherapy dose intensity based on post-treatment blood counts.

A Prognostic Model Using Post-Steroid Neutrophil-Lymphocyte Ratio Predicts Overall Survival in Primary Central Nervous System Lymphoma.

Background: Ratios of differential blood counts (hematological indices, HIs) had been identified as prognostic variables in various cancers. In primary central nervous system lymphomas (PCNSLs), higher baseline neutrophil-lymphocyte ratio (NLR) in particular was found to portend a worse overall survival. However, it was often observed that differential counts shift drastically following steroid administration. Moreover, steroids are an important part of the arsenal against PCNSL due to its potent lymphotoxic effects. We showed that the effect of steroids on differential blood cell counts and HIs could be an early biomarker for subsequent progression-free (PFS) and overall survival (OS). Methods: This study retrospectively identified all adult patients who received a brain biopsy from 2008 to 2019 and had histologically confirmed PCNSL, and included only those who received chemoimmunotherapy, with documented use of corticosteroids prior to treatment induction. Different blood cell counts and HIs were calculated at three time-points: baseline (pre steroid), pre chemoimmunotherapy (post steroid) and post chemoimmunotherapy. Tumor progression and survival data were collected and analyzed through Kaplan−Meier estimates and Cox regression. We then utilized selected variables found to be significant on Kaplan−Meier analysis to generate a decision-tree prognostic model, the NNI-NCCS score. Results: A total of 75 patients who received chemoimmunotherapy were included in the final analysis. For NLR, OS was longer with higher pre-chemoimmunotherapy (post-steroid) NLR (dichotomized at NLR ≥ 4.0, HR 0.42, 95% CI: 0.21−0.83, p = 0.01) only. For platelet-lymphocyte ratio (PLR) and lymphocyte-monocyte ratio (LMR), OS was better for lower post-chemoimmunotherapy PLR (dichotomized at PLR ≥ 241, HR 2.27, 95% CI: 1.00 to 5.18, p = 0.05) and lower pre-chemoimmunotherapy (post-steroid) LMR (dichotomized at LMR ≥25.7, HR 2.17, 95% CI: 1.10 to 4.31, p = 0.03), respectively, only. The decision-tree model using age ≤70, post-steroid NLR >4.0, and pre-steroid (baseline) NLR <2.5 and the division of patients into three risk profiles­low, medium, and high­achieved good accuracy (area-under-curve of 0.78), with good calibration (Brier score: 0.16) for predicting 2-year overall survival. Conclusion: We found that post-steroid NLR, when considered together with baseline NLR, has prognostic value, and incorporation into a prognostic model allowed for accurate and well-calibrated stratification into three risk groups.

Hope, bias and survival expectations of advanced cancer patients: A cross-sectional study.

OBJECTIVE: Many patients with advanced illness are unrealistically optimistic about their prognosis. We test for the presence of several cognitive biases, including optimism bias, illusion of superiority, self-deception, misattribution, and optimistic update bias, that could explain unrealistically optimistic prognostic beliefs among advanced cancer patients and quantifies the extent to which hope exacerbates these biases. METHODS: A cross-sectional survey was administered to 200 advanced cancer patients with physician-estimated prognoses of one year or less. Hope was measured using the Herth Hope Index (HHI). Hypotheses were tested using linear and logistic regressions and a structural-equation model. RESULTS: Results are consistent with the presence of optimism bias, illusion of superiority, self-deception, and misattribution. All of these biases are amplified by higher levels of hope. Each 1-point higher HHI is associated with a 6% (OR: 1.06; 95% CI: 1.01-1.11) greater odds of believing their illness is curable, a 0.33-year (95% CI: 0.17-0.49) longer expected survival, a 6% (OR: 1.06; 95% CI: 1.02-1.11) higher probability of believing that survival outcomes are better than the average patient, a 5% higher odds of believing primary intent of treatment is curative (OR: 1.05; 95% CI: 1.00-1.10), and a 12% (OR: 1.12; 95% CI: 1.05-1.17) higher odds of believing they are well-informed. Mediation analyses revealed that hope significantly mediates the effect of mental-well-being and loneliness on expected survival. CONCLUSIONS: Results suggest advanced cancer patients succumb to several cognitive biases which are exacerbated by greater levels of hope. As a result, they are susceptible to possible over-treatment and regret.