The association of nutritional and inflammatory biomarkers with overall survival in patients with non-small-cell lung cancer treated with immune checkpoint inhibitors.

OBJECTIVES: Pretreatment biomarkers are needed to identify patients with non-small-cell lung cancer (NSCLC) likely to have worse survival. This ensures that only patients with a real chance of benefit receive immune checkpoint inhibitor (ICI) treatment. In this study, we examined the associations of baseline nutritional and inflammatory biomarkers with overall survival in a real-world cohort of NSCLC patients who received ICIs. MATERIALS AND METHODS: We used prospectively collected data from the OncoLifeS data biobank. The cohort included 500 advanced-stage NSCLC patients treated with ICIs from May 2015 to June 2021. Biomarkers were evaluated within 2 weeks before ICI treatment: neutrophil-to-lymphocyte ratio, C-reactive protein (CRP), Glasgow prognostic score, CRP/albumin ratio (CAR), prognostic nutritional index (PNI), and advanced lung cancer inflammation index. For each biomarker, low- and high-risk groups were defined using literature-based cut-offs. Adjusted hazard ratios (aHRs) and 95% confidence intervals (95% CIs) were estimated using adjusted survival analysis. RESULTS: Most patients were male (60.8%), the mean baseline age was 65 ± 9 years, and 88% had stage IV disease. For each biomarker, low-risk patients had better overall survival (all, p < 0.001), with CAR and PNI showing the strongest associations. In multivariable analyses a combined CAR/PNI risk score had a stronger association with overall survival (aHR 3.09, 95% CI 2.36-4.06) than CAR alone (aHR 2.22, 95% CI 1.79-2.76) or PNI alone (aHR 2.09, 95% CI 1.66-2.61). CONCLUSION: These results highlight the potential value of nutritional and inflammatory biomarkers, in particular CAR and PNI, in identifying NSCLC patients with highest mortality risk before starting ICI treatment.

Influenza season influence on outcome of new nodules in the NELSON study.

We evaluated the impact of the influenza season on outcome of new lung nodules in a LDCT lung cancer screening trial population. NELSON-trial participants with ≥ 1 new nodule detected in screening rounds two and three were included. Outcome (resolution or persistence) of new nodules detected per season was calculated and compared. Winter (influenza season) was defined as 1st October to 31st March, and compared to the summer (hay-fever season), 1st April to 30th September. Overall, 820 new nodules were reported in 529 participants. Of the total new nodules, 482 (59%) were reported during winter. When considering the outcome of all new nodules, there was no statistically significant association between summer and resolving nodules (OR 1.07 [CI 1.00-1.15], p = 0.066), also when looking at the largest nodule per participant (OR 1.37 [CI 0.95-1.98], p = 0.094). Similarly, there was no statistically significant association between season and screen detected cancers (OR 0.47 [CI 0.18-1.23], p = 0.123). To conclude, in this lung cancer screening population, there was no statistically significant association between influenza season and outcome of new lung nodules. Hence, we recommend new nodule management strategy is not influenced by the season in which the nodule is detected.

Quality of life after treatment with immune checkpoint inhibitors for lung cancer; the impact of age.

INTRODUCTION: Immune checkpoint inhibitors (ICIs) have revolutionized lung cancer treatment. However, it remains unclear as to whether changes in Health-Related Quality-of-Life (HRQoL) are associated with the age of lung cancer patients treated using ICIs. This study aimed to evaluate this possible association and to compare ICI-treated patients' HRQoL scores with normative data of an age-matched non-cancer general population. METHODS: Lung cancer patients from the OncoLifeS data-biobank were included if they were treated with ICIs, irrespective of other treatments, at the University Medical Center Groningen between 2015 and 2021 and had completed the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire C30 (EORTCQLQ-C30), both at the start of ICI treatment and after six months. Association of age as a continuous variable (per 10 years) and changes in HRQoL scores between baseline and 6 months was assessed using multivariable regression analyses. Clinical relevance of differences in HRQoL scores between OncoLifeS and the general population was classified into trivial, small, medium, and large, for three age groups (<60, 60-69 and ≥ 70 years). RESULTS: 151 patients were included with a mean age of 65.8 years. An increase in age per 10 years was associated with a larger decrease in the summary HRQoL score(ß = -3.28,CI95%-6.42;-0.14), physical(ß = -4.8, CI95% -8.71;-0.88), cognitive(ß = -4.51,CI95%-8.24;-0.78), role functioning(ß = -5.41,CI95%-10.78;-0.05), symptom burden(ß = -3.66,CI95%-6.6;-0.73), and smaller negative changes in financial difficulties(ß = 6.5 95 % CI 3.16; 9.85). OncoLifeS HRQoL scores were lower than those of the general population and differences were most often classified as large and medium. CONCLUSION: Older lung cancer patients experience larger deteriorations in most HRQoL domains after 6 months of ICI treatment. Also, these patients showed significantly lower HRQoL scores compared to the general population.

Changes in quantitative CT image features of ground-glass nodules in differentiating invasive pulmonary adenocarcinoma from benign and in situ lesions: histopathological comparisons.

AIM: To evaluate progressive changes in quantitative CT features of the non-solid component of ground-glass nodules (GGNs) from baseline to follow-up to differentiate invasive (minimally invasive adenocarcinoma [MIA] and invasive adenocarcinoma [IA]) GGNs from benign or pre-invasive (adenocarcinoma in situ [AIS]) lesions. MATERIALS AND METHODS: Patients with a GGN detected at baseline and follow-up computed tomography (CT), examined by tissue sampling were included in the study. The diameter and mean, maximum, minimum CT density and density deviation from the non-solid component of whole GGNs were measured. Progression of these features over time was analysed by linear regression analysis. Multivariate receiver operating characteristics analyses of combined measures created by a logistic regression model were performed to evaluate diagnostic performance for invasive GGNs. RESULTS: Sixty-one patients (24 males) with 70 GGNs were included. Fifteen GGNs were benign, six AIS, 38 MIA, and 11 IA. The mean diameter of all histological subtypes increased from baseline to follow-up, the largest increase was found in the MIA group (p<0.001). For MIA and IA, the mean, maximum, minimum density, and density deviation had a positive correlation over time, whilst benign and pre-invasive GGNs showed a negative correlation for these features. A diagnostic model based on three GGN features (increasing in diameter, mean density, and density deviation) identified invasive GGNs with a sensitivity, specificity and area under the receiver operating characteristic (ROC) curve (AUC) of 83.7%, 61.9%, and 0.786, respectively (p<0.001). CONCLUSION: In GGN follow-up, the diameter of benign and AIS, and invasive GGNs significantly increased. Additional analysis of mean density and density deviation in the non-solid component may help to identify invasive GGNs.

Screening for lung cancer by imaging: the Nelson study.

The NELSON trial is the first randomised lung cancer screening trial in which pulmonary nodule management is based on volumetry. This led to considerably less false-positive referrals compared to other lung cancer screening trials, with very high negative predictive values found in the first and second screening rounds. Mortality results are still pending, but the knowledge already gained in the NELSON trial and its side-studies provide valuable information in the field of screening for lung cancer.