Comorbidity in Lung Cancer: A Prospective Cohort Study of Self-Reported versus Register-Based Comorbidity

Development of a machine learning-based risk model for postoperative complications of lung cancer surgery

PURPOSE

To develop a comorbidity risk score specifically for lung resection surgeries.

METHODS

We reviewed the medical records of patients who underwent lung resections for lung cancer, and developed a risk model using data from 2014 to 2017 (training dataset), validated using data from 2018 to 2019 (validation dataset). Forty variables were analyzed, including 35 factors related to the patient's overall condition and five factors related to surgical techniques and tumor-related factors. The risk model for postoperative complications was developed using an elastic net regularized generalized linear model. The performance of the risk model was evaluated using receiver operating characteristic curves and compared with the Charlson Comorbidity Index (CCI).

RESULTS

The rate of postoperative complications was 34.7% in the training dataset and 21.9% in the validation dataset. The final model consisted of 20 variables, including age, surgical-related factors, respiratory function tests, and comorbidities, such as chronic obstructive pulmonary disease, a history of ischemic heart disease, and 12 blood test results. The area under the curve (AUC) for the developed risk model was 0.734, whereas the AUC for the CCI was 0.521 in the validation dataset.

CONCLUSIONS

The new machine learning model could predict postoperative complications with acceptable accuracy.

CLINICAL REGISTRATION NUMBER

2020-0375.

Pain management for post-treatment survivors of complex cancers: a qualitative study of opioids and cannabis

Aim: We aimed to understand experiences with opioids and cannabis for post-treatment cancer survivors. Patients & methods: We conducted seven focus groups among head and neck and lung cancer survivors, using standard qualitative methodology to explore themes around 1) post-treatment pain and 2) utilization, perceived benefits and perceived harms of cannabis and opioids. Results & conclusion: Survivors (N = 25) experienced addiction fears, stigma and access challenges for both products. Opioids were often perceived as critical for severe pain. Cannabis reduced pain and anxiety for many survivors, suggesting that anxiety screening, as recommended in guidelines, would improve traditional pain assessment. Opioids and cannabis present complex harms and benefits for post-treatment survivors who must balance pain management and minimizing side effects.

Comorbidity in limited disease small-cell lung cancer: Age-adjusted Charlson comorbidity index and its association with overall survival following chemoradiotherapy

Background

Combined, platinum-based thoracic chemoradiotherapy (TCR) is the current state-of-the-art treatment for patients with limited disease (LD) small-cell lung cancer (SCLC). There is only limited data available regarding the effect of comorbidities on survival following TRC. The purpose of this study is to assess the age-adjusted Charlson comorbidity index (ACCI) as a predictor of overall survival in LD-SCLC patients undergoing TCR.

Patients and methods

We retrospectively analyzed 367 SCLC patients diagnosed with LD-SCLC who received TCR between 2003 and 2017. We evaluated the ACCI (n = 348) as a predictor of overall survival (OS). In this cohort, 322 patients (88%) received platinum-based TCR (either cisplatin or carboplatin), and 37 (10%) patients received vincristine based TCR. Median radiation dose was 60 Gy (range 24-66 Gy). Additionally, 83% of patients (n = 303) received prophylactic cranial irradiation (PCI, 30 Gy in 2 Gy fractions). Kaplan-Meier survival analysis was performed for OS. For comparison of survival curves, Log-rank (Mantel-Cox) test was used. Univariate and multivariate Cox proportional-hazards ratios (HRs) were used to assess the influence of cofactors on OS.

Results

Patients with an ACCI > 6 had a significantly shorter OS compared with patients with an ACCI ≤ 6 (median 11 vs. 20 months; p = 0.005). Univariate analysis for OS revealed a statistically significant effect for ACCI > 6 (HR 1.7; 95% CI 1.2-2.4; p = 0.003), PCI (HR 0.5; 95% CI 0.3-0.7; p < 0.001), and Karnofsky performance status ≤ 70% (KPS) (HR 1.4; 95% CI 1.1-1.90; p = 0.015). In multivariate analysis, OS was significantly associated with PCI (HR 0.6; 95% CI 0.4-0.9; p = 0.022) and ACCI > 6 (HR 1.5; 95% CI 1.0-2.1; p = 0.049).

Conclusion

Comorbidity is significantly associated with survival in patients with LD-SCLC undergoing TCR. The ACCI may be a valuable tool to identify patients with a shorter survival and thus might be used for risk stratification and oncological decision making.

Older patients with EGFR mutation-positive non-small cell lung cancer treated with afatinib in clinical practice: A subset analysis of the non-interventional GIDEON study

INTRODUCTION

Lung cancer is most common in older patients; despite this, older patients are historically under-represented in clinical studies. Here we present data from GIDEON, a study undertaken in Germany in patients with epidermal growth factor receptor mutation-positive (EGFRm+) non-small cell lung cancer (NSCLC) receiving first-line afatinib. GIDEON enrolled a high proportion of patients aged ≥70 years, providing an opportunity to study afatinib use in older patients.

MATERIALS AND METHODS

In GIDEON (NCT02047903), a prospective non-interventional study, patients with EGFRm+ NSCLC received first-line afatinib in routine clinical practice until disease progression, death or intolerable adverse events. Key objectives were twelve-month progression-free survival (PFS) rate and objective response rate (ORR). Overall survival (OS) and safety were also assessed. This post hoc analysis explores outcomes of patients grouped by age (≥70 and <70 years).

RESULTS

In the 152 patients enrolled in GIDEON (69.7% female, 64.5%/22.4%/13.2% with Del19/L858R/other exon 18-21 mutations, 33.6% with brain metastases), the median age was 67 years (range 38-89) and 43.4% were aged ≥70 years. In the ≥70 years age group and the <70 years age group, twelve-month PFS rate was 58.9% and 43.9%, median PFS was 17.2 months and 10.6 months, ORR was 72.0% and 76.5%, twelve-month OS rate was 79.1% and 79.2%, 24-month OS rate was 52.0% and 61.7%, and median OS was 30.4 months and 27.4 months, respectively. In the ≥70 years age group and the <70 years age group, grade ≥3 adverse drug reactions (ADRs) were observed in 34.8% and 40.7% of patients, respectively; the most common were diarrhea (13.6% and 14.0%), acneiform dermatitis (7.6% and 7.0%), stomatitis (1.5% and 4.7%) and maculopapular rash (1.5% and 4.7%).

DISCUSSION

Patients with EGFRm+ NSCLC aged ≥70 years showed clinical benefit from first-line afatinib with no unexpected safety signals, supporting the use of afatinib in this setting.

Clinical and Biological Variables Influencing Outcome in Patients with Advanced Non-Small Cell Lung Cancer (NSCLC) Treated with Anti-PD-1/PD-L1 Antibodies: A Prospective Multicentre Study

Introduction: Immune checkpoint inhibitors (ICIs) have become the standard of treatment for patients with non-small cell lung cancer (NSCLC). However, there are still many uncertainties regarding the selection of the patient who could benefit more from this treatment. This study aims to evaluate the prognostic and predictive role of clinical and biological variables in unselected patients with advanced NSCLC candidates to receive ICIs. Methods: This is an observational and prospective study. The primary objective is the evaluation of the relationship between clinical and biological variables and the response to ICIs. Secondary objectives included: safety; assessment of the relationship between clinical and biological parameters/concomitant treatments and progression-free survival at 6 months and overall survival at 6 and 12 months. Nomograms to predict these outcomes have been generated. Results: A total of 166 patients were included. An association with response was found in the presence of the high immunohistochemical PD-L1 expression, squamous cell histotype, and early line of treatment, whereas a higher probability of progression was seen in the presence of anemia, high LDH values and neutrophil/lymphocyte ratio (NLR), pleural involvement, and thrombosis before treatment. The nomogram showed that anemia, PD-L1 expression, NLR, and LDH represented the most informative predictor as regards the three parameters of interest. Conclusions: In the era of personalized medicine, the results are useful for stratifying the patients and tailoring the treatments, considering both the histological findings and the clinical features of the patients.

Inflammation-scores as prognostic markers of overall survival in lung cancer: a register-based study of 6,210 Danish lung cancer patients

Background

Inflammation-scores based on general inflammation markers are suggested as prognostic markers of overall survival (OS) in lung cancer. However, whether these inflammation-scores improves the prognostication performed by well-established prognostic markers is unsettled. In a large register-based lung cancer patient cohort, nine different inflammation-scores were compared, and their ability to optimize the prognostication of OS was evaluated.

Methods

Lung cancer patients diagnosed from 2009–2018 in The Central Denmark Region were identified in the Danish Lung Cancer Registry. Pre-treatment inflammation markers were extracted from the clinical laboratory information system. Prognostication of OS was evaluated by Cox proportional hazard models. Comparison of the inflammation-scores and their added value to established prognostic markers were assessed by Akaike's information criteria and Harrel's C-index.

Results

In total, 5,320 patients with non-small cell lung cancer (NSCLC) and 890 patients with small cell lung cancer (SCLC) were identified. In NSCLC, the Aarhus composite biomarker score (ACBS), including albumin, C-reactive protein, neutrophil count, lymphocyte count and haemoglobin, and the neutrophil-lymphocyte-ratio (NLR) were superior. Furthermore, they improved the prognostication of OS significantly (p <0.0001) (ACBS: HR: 2.24 (95%CI: 1.97–2.54); NLR: HR: 1.58 (95%CI: 1.47 – 1.69)). In SCLC, three scores were equally superior and improved the prognostication of OS p < 0.0001): neutrophil–lymphocyte-ratio (HR:1.62 (95%CI: 1.38–1.90)), modified Glasgow Prognostic Score (mGPS) (HR:1.70 (95%CI: 1.55–1.86) and the Combined NLR and GPS (CNG) (HR:2.10 (95%CI: 1.77–2.49).

Conclusions

The ACBS was the optimal score in NSCLC, whereas neutrophil–lymphocyte-ratio, mGPS and CNG were equally superior in SCLC. Additionally, these inflammation-scores all optimised the prognostication of OS and added value to well-established prognostic markers.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-09108-5.

A narrative review of prognosis prediction models for non-small cell lung cancer: what kind of predictors should be selected and how to improve models?

Objective

To discover potential predictors and explore how to build better models by summarizing the existing prognostic prediction models of non-small cell lung cancer (NSCLC).

Background

Research on clinical prediction models of NSCLC has experienced explosive growth in recent years. As more predictors of prognosis are discovered, the choice of predictors to build models is particularly important, and in the background of more applications of next-generation sequencing technology, gene-related predictors are widely used. As it is more convenient to obtain samples and follow-up data, the prognostic model is preferred by researchers.

Methods

PubMed and the Cochrane Library were searched using the items “NSCLC”, “prognostic model”, “prognosis prediction”, and “survival prediction” from 1 January 1980 to 5 May 2021. Reference lists from articles were reviewed and relevant articles were identified.

Conclusions

The performance of gene-related models has not obviously improved. Relative to the innovation and diversity of predictors, it is more important to establish a highly stable model that is convenient for clinical application. Most of the prevalent models are highly biased and referring to PROBAST at the beginning of the study may be able to significantly control the bias. Existing models should be validated in a large external dataset to make a meaningful comparison.

The role of multimorbidity in short-term mortality of lung cancer patients in Spain: a population-based cohort study

AIM

Chronic diseases often occur simultaneously and tend to be associated with adverse health outcomes, but limited research has been undertaken to understand their role in lung cancer mortality. Therefore, this study aims to describe the prevalence and patterns of having one (comorbidity) or ≥ 2 chronic diseases (multimorbidity) among lung cancer patients in Spain, and to examine the association between comorbidity or multimorbidity and short-term mortality risk at six months after cancer diagnosis.

METHODS

In this population-based cohort study, data were drawn from two Spanish population-based cancer registries, Girona and Granada, and electronic health records. We identified 1259 adult lung cancer patients, diagnosed from 1st January 2011 to 31st December 2012. We identified the most common patterns of individual comorbidities and their pairwise correlations. We used a flexible parametric modelling approach to assess the overall short-term mortality risk 6 months after cancer diagnosis by levels of comorbidity after adjusting for age, sex, smoking status, province of residence, surgery, cancer stage, histology, and body mass index.

RESULTS

We found high prevalence of comorbidity in lung cancer patients, especially among the elderly, men, those diagnosed with advanced-stage tumours, smokers, and obese patients. The most frequent comorbidities were chronic obstructive pulmonary disease (36.6%), diabetes (20.7%) and heart failure (16.8%). The strongest pairwise correlation was the combination of heart failure with renal disease (r = 0.20, p < 0.01), and heart failure with diabetes (r = 0.16, p < 0.01). Patients with either one or two or more comorbidities had 40% higher overall mortality risk than those without comorbidities (aHR for comorbidity: 1.4, 95%CI: 1.1-1.7; aHR for multimorbidity: 1.4, 95%CI: 1.1-1.8), when relevant confounding factors were considered.

CONCLUSIONS

The presence of comorbid diseases, rather than the number of comorbidities, was associated with increasing the risk of short-term lung cancer mortality in Spain. Comorbidity was a consistent and independent predictor of mortality among lung cancer patients, six months after diagnosis. The most common comorbid conditions were age-, obesity- and tobacco-related diseases. Our findings highlight the need to develop targeted preventive interventions and more personalised clinical guidelines to address the needs of lung cancer patients with one or more comorbidities in Spain.

Comorbidity in lung cancer patients and its association with hospital readmission and fatality in China

BACKGROUND

Comorbidity has been established as one of the important predictors of poor prognosis in lung cancer. In this study, we analyzed the prevalence of main comorbidities and its association with hospital readmission and fatality for lung cancer patients in China.

METHODS

The analyses are based on China Urban Employees' Basic Medical insurance (UEBMI) and Urban Residents' Basic Medical Insurance (URBMI) claims database and Hospital Information System (HIS) Database in the Beijing University Cancer Hospital in 2013-2016. We use Elixhauser Comorbidity Index to identify main types of comorbidities.

RESULTS

Among 10,175 lung cancer patients, 32.2% had at least one comorbid condition, and the proportion of patients with one, two, and three or more comorbidities was 21.7, 8.3 and 2.2%, respectively. The most prevalent comorbidities identified were other malignancy (7.5%), hypertension (5.4%), pulmonary disease (3.7%), diabetes mellitus (2.5%), cardiovascular disease (2.4%) and liver disease (2.3%). The predicted probability of having comorbidity and the predicted number of comorbidities was higher for middle elderly age groups, and then decreased among patients older than 85 years. Comorbidity was positively associated with increased risk of 31-days readmission and in-hospital death.

CONCLUSION

Our study is the first to provide an overview of comorbidity among lung cancer patients in China, underlines the necessity of incorporating comorbidity in the design of screening, treatment and management of lung cancer patients in China.

Management and outcomes of patients with chronic obstructive lung disease and lung cancer in a public healthcare system

Hypothesis

There is limited data on the care and outcomes of individuals with both chronic obstructive pulmonary disease (COPD) and lung cancer, particularly in advanced disease. We hypothesized such patients would receive less cancer treatment and have worse outcomes.

Methods

We analyzed administrative data from the province of Ontario including demographics, hospitalization records, physician billings, cancer diagnosis, and treatments. COPD was defined using the ICES-derived COPD cohort (1996–2014) with data from 2002 to 2014. Descriptive statistics and multivariable analyses were undertaken.

Results

Of 105 304 individuals with lung cancer, 43 375 (41%) had stage data and 36 738 (34.9%) had COPD. Those with COPD were likely to be younger, have a Charlson score ≤ 1, have lower income, to live rurally, and to have stage I/II lung cancer (29.8 vs 26.5%; all p<0.001). For the COPD population with stage I/II cancer, surgery and adjuvant chemotherapy were less likely (56.8 vs. 65.9% and 15.4 vs. 17.1%, respectively), while radiation was more likely (26.0 vs. 21.8%) (p all < 0.001). In the stage III/IV population, individuals with COPD received less chemotherapy (55.9 vs 64.4%) or radiation (42.5 vs 47.5%; all p<0.001). Inhaler and oxygen use was higher those with COPD, as were hospitalizations for respiratory infections and COPD exacerbations. On multivariable analysis, overall survival was worse among those with COPD (HR 1.20, 95% CI 1.19–1.22).

Conclusions

A co-diagnosis of COPD and lung cancer is associated with less curative treatment in early stage disease, less palliative treatment in late stage disease, and poorer outcomes.

cGAS-STING pathway expression as a prognostic tool in NSCLC

Background

Disease recurrence in localized lung adenocarcinoma is a major obstacle for improving the overall outcome of lung cancer. Thus, better prognostic biomarkers are needed to identify patients at risk. In order to clear cancer, immune detection of tumor cells is of vital importance. DNA-leakage into the cytosol and tumor environment is one important tumor-associated danger signal and cGAS is a pivotal DNA-sensor that detects misplaced DNA and initiates an innate immune response. In this study, we investigate the cGAS-STING-pathway expression in tumor tissue and circulating immune cells from lung adenocarcinoma patients in relation to stage of disease and overall survival (OS).

Methods

Gene expression was measured using target specific droplet digital polymerase chain reaction (ddPCR) assays in a cohort of 80 patients with lung adenocarcinoma and 45 patients suspected of lung cancer, but determined to be cancer-free. The expression values were correlated to stage of disease. For further exploration of stage dependent expression, we used a publicly available gene expression data set to stratify patients by stage and correlate gene expression to OS.

Results

In both tumor tissue and peripheral blood mononuclear cells (PBMCs) from cancer patients, we observed differential expression of cGAS-STING pathway components compared to cancer-free individuals. Furthermore, cGAS-STING pathway expression was elevated in PBMCs from patients with localized disease (stage I and II) compared to patients with metastatic disease (stage III and IV). Survival analysis based on publicly available gene expression data sets demonstrated a superior OS for patients with localized disease and high levels of cGAS, STING and TBK1.

Conclusions

The expression of the cGAS-STING pathway is stage dependent and high expression is correlated with localized adenocarcinoma. For patients with localized disease, high cGAS, STING and TBK1 expression correlated with improved OS and may be a potential biomarker for this patient subgroup.

Comorbidity among Danish lung cancer patients before and after initial cancer diagnosis

Objective: Lung cancer is the leading cause of cancer-related death worldwide. This population-based longitudinal study investigates survival rates and the burden of comorbidity before and after being diagnosed with lung cancer in Denmark. Methods: From the Danish National Patient Registry (NPR) and the Danish Civil Registration System (CPR), 53,749 patients with lung cancer were identified and matched with 214,304 controls on age, gender, region of residence and marital status in the period 1998-2010. From the NPR, data on survival and comorbidity, registered as ICD-10 diagnoses, were extracted. Comorbidity was assessed using the Deyo-Charlson comorbidity score (DCcs) and mortality using Kaplan-Meier survival curves. Results: 1-year survival rate for Danish lung cancer patients was 51.7 % (CI 51.3-52.1) and 5-year survival rate was 14.7 % (CI 14.3-15.0) compared to 96.8 % (CI 96.7-96.8) and 84.0 % (CI 83.9-84.2) for controls respectively. Overall, cases had significantly more comorbidity compared to controls before being diagnosed with lung cancer. Prior to being diagnosed with lung cancer, more cases than controls had been diagnosed with other malignancies (11.4 % vs 6.0 % p<0.005), diseases of the circulatory system (16.4 % vs 13.0 % p<0.005) and respiratory diseases (12.2 % vs 4.8 % p<0.005). Among lung cancer patients 21.8 % had a DCcs ≥ 1 compared to 13.3 % among controls (P<0.005). The 1-year survival for DCcs =0 was 54.8 % (CI 54.3-55.3) for lung cancer patients and 97.8 % (CI 97.7-97.9) for controls. Decreasing survival with increasing DCcs was found in both groups. Conclusion: This study provides unique nationwide comorbidity data on patients before and after being diagnosed with lung cancer. We found increased mortality with increasing comorbidity, however more pronounced among controls compared to patients with lung cancer.

Impact of deprivation and comorbidity on outcomes in emergency general surgery: an epidemiological study

Background

The impact of socioeconomic deprivation and comorbidities on the outcome of patients who require emergency general surgery (EGS) admission is poorly understood. The aim of this study was to examine the effect of deprivation and comorbidity on mortality, discharge destination and length of hospital stay (LOS) in patients undergoing EGS in Scotland.

Methods

Prospectively collected data from all Scottish adult patients (aged >15 years) requiring EGS admitted between 1997 and 2016 were obtained from the Scottish Government. Data included age, sex, Scottish Index of Multiple Deprivation (SIMD), 5-year Charlson Comorbidity Index (CCI), whether an operation took place and outcomes including mortality, discharge destination and LOS. Logistic regression was used for the analysis of mortality and discharge destination and Poisson regression was used for LOS.

Results

1 477 810 EGS admissions were analyzed. 16.2% were in the most deprived SIMD decile and 5.6% in the least deprived SIMD decile. 75.6% had no comorbidity, 20.3% had mild comorbidity, 2.5% had moderate comorbidity and 1.6% had severe comorbidity. 78.6% were discharged directly home. Inpatient, 30-day, 90-day and 1-year crude mortality was 1.7%, 3.7%, 7.2% and 12.4%, respectively. Logistic regression showed that severe comorbidity was associated with not being discharged directly to home (OR 0.38, 95% CI 0.37 to 0.39) and higher inpatient mortality (OR 13.74, 95% CI 13.09 to 14.42). Compared with the most affluent population, the most deprived population were less likely to be discharged directly to home (OR 0.97, 95% CI 0.95 to 0.99) and had higher inpatient mortality (OR 1.36, 95% CI 1.8 to 1.46). Poisson analysis showed that severe comorbidity (OR 1.69, 95% CI 1.68 to 1.69) and socioeconomic deprivation (OR 1.11, 95% CI 1.11 to 1.12) were associated with longer LOS.

Discussion

Increased levels of comorbidity and, to a lesser extent, socioeconomic deprivation are key drivers of mortality, discharge destination and LOS following admission to an EGS service.

Level of evidence

III (prospective/retrospective with up to two negative criteria).

Study type

Epidemiological/prognostic.

A Cohort Study of Exposure to Antihyperglycemic Therapy and Survival in Patients with Lung Cancer

We evaluated the effect of antihyperglycemic therapy on the survival of patients with lung cancer (LC). The analysis included patients with LC and concomitant type 2 diabetes. 15,929 patients were classified into five groups: metformin users, insulin users, metformin and insulin users, sulphonylurea users and non-diabetic group. A multivariate analysis showed that exposure to either metformin or to insulin was associated with a lower risk of LC-specific mortality, and this approached statistical significance (HR 0.82, 95% CI 0.72–92 for metformin and HR 0.65, 95% CI 0.44–95 for insulin). When deaths from all causes were considered, only metformin exposure was associated with a significantly lower risk of death (HR 0.82, 95% CI 0.73–0.92). Users of sulphonylurea were at a higher risk of LC-specific and overall mortality (HRs 1.19, 95% CI 0.99–1.43 and 1.22, 95% CI 1.03–1.45). Our study shows a positive effect of metformin on the survival of patients with LC. Moreover, our results show that exposure to insulin was associated with a lower risk of LC-specific mortality, but not with deaths from all causes. The study results suggested that users of sulphonylurea may be at a higher risk of LC-specific and overall mortality.

Computed Tomography Histogram Approach to Predict Lymph Node Metastasis in Patients With Clinical Stage IA Lung Cancer

BACKGROUND

Quantitative computed tomography (CT) histogram analysis of tumors is reported to help distinguish between invasive and less invasive lung cancers. This study aimed to clarify whether CT histogram analysis of tumors can be used to classify patients with clinical stage 0 to IA non-small cell lung cancer according to pathologic lymph node (pN) status.

METHODS

Predictive factors associated with pN metastasis were identified from the derivation dataset including 629 patients with clinical stage 0 to IA non-small cell lung cancer who underwent complete resection with lymph node dissection (surgeries between 2008 and 2013). The validation dataset including 238 patients (surgeries between 2014 and 2015) were subsequently reevaluated. Clinicosurgical factors, including CT histogram analysis of tumors (CT value percentiles 2.5, 25, 50, 75, and 97.5, skewness, and kurtosis) were assessed.

RESULTS

Seventy-three patients (12%) in the derivation cohort and 35 patients (15%) in the validation cohort had positive nodes. The pN status significantly affected survival in the entire population: 5-year overall survival of 93.1% vs 71.1% and 5-year disease-free survival of 85.9% vs 43.1% for negative vs positive (both P < .001). On multivariate analysis in the derivation cohort, the 75th percentile CT value (P < .001), age (P = .003), and comorbidities (P = .006) were significantly associated with pN metastasis. The area under the curve and the cutoff level of the 75th percentile CT value relevant to pN metastasis were 0.729 and 1.5 HU, respectively, and the threshold value provided accuracy of 71% for the validation cohort.

CONCLUSIONS

Histogram analysis of CT imaging metrics of tumors contributes to noninvasive prediction of pN metastasis in patients with clinical stage 0 to IA non-small cell lung cancer.

The prognostic role of inflammation-scores on overall survival in lung cancer patients

OBJECTIVE

Inflammation has been validated as a host-related prognostic marker in cancer. The Glasgow Prognostic score (GPS) and neutrophil-to-lymphocyte ratio (NLR) are suggested measures of inflammation. However, the allocation of patients has been questioned. Hence, optimized inflammation-scores has been developed, such as the combined NLR and GPS (CNG) system, and the Aarhus composite biomarker score (ACBS). So far, these optimized inflammation-scores have not been validated in lung cancer patients. We evaluated if the optimized inflammation-scores were prognostic markers of inferior survival in lung cancer patients. Furthermore, we tested which of the optimized inflammation-scores led to better patient-allocation.

MATERIAL AND METHODS

The cohort of this prospective study composed of 275 non-small cell lung cancer patients. We evaluated pre-diagnostic serum biomarkers for GPR, NLR, platelet-to-lymphocyte ratio as well as the optimized inflammation-scores CNG and ABCS as predictors of overall survival (OS), and we examined the patient-allocation derived from each inflammation-score.

RESULTS

Each of the evaluated inflammation-scores could predict the overall survival even when adjustments were made for comorbidity and clinicopathological characteristics. When comparing the scores, the optimized inflammation-scores CNG and ACBS led to a better and more balanced patient-allocation. In the early clinical stages I & II, the optimized scores could reveal a subgroup of patients with poorer survival that is similar to stage III.

CONCLUSION

In this cohort of lung cancer patients, we demonstrate that inflammation-scores are prognostic markers of inferior survival. Furthermore, we demonstrate that the optimized inflammation-scores CNG and ACBS lead to better patient-allocation independently of the clinicopathological characteristics and comorbidity.

Defining Optimal Comorbidity Measures for Patients With Early-Stage Non-small cell lung cancer Treated With Stereotactic Body Radiation Therapy

PURPOSE

Comparison of overall survival (OS) between stereotactic body radiation therapy (SBRT) and other treatments for early-stage non-small cell lung cancer is confounded by differences in age, performance status, and medical comorbidity. We sought to define the most robust measurement for this population among 5 indices: age, Eastern Cooperative Oncology Group performance status, Adult Comorbidity Evaluation 27, Charlson Comorbidity Index (CCI), and age-adjusted CCI (CCIa).

METHODS AND MATERIALS

A total of 548 patients with stage I non-small cell lung cancer treated with SBRT were analyzed. Patients were divided into high- and low-risk groups for OS for each index using the log-rank test. Continuous and dichotomized models were compared via Akaike information criterion and the Vuong test. Multivariate Cox regression modeling was used with demographic information to determine the independent prognostic value of the continuous and dichotomized versions of the indices. The best was used to stratify the patients into as many significantly different cohorts as possible.

RESULTS

Optimal cut-points between high-risk and low-risk OS groups for age, Eastern Cooperative Oncology Group status, Adult Comorbidity Evaluation 27, CCI, and CCIa were ≥75 years, ≥1, ≥3, ≥3, and ≥6 with hazard ratios for death of 1.23 (95% confidence interval, 1.00-1.50), 1.66 (1.28-2.15), 1.37 (1.12-1.67), 1.43 (1.17-1.76), and 1.47 (1.20-1.80), respectively. Dichotomizing did not result in a significant loss of prognostic power. Although there was no significant difference in prognostic power among the indices, CCIa best predicted OS. CCIa divided the patients into 3 cohorts with median OS of 42 months, 33 months, and 23 months for scores of ≤5, 6 to 7, and ≥8, respectively.

CONCLUSIONS

CCIa was the best indicator of OS in every model employed with no loss of prognostic power with dichotomization. Dichotomization of CCIa (≥6) could be implemented in future comparisons of SBRT with OS. No cohort could be identified with a median survival of less than a year, for which treatment could be deemed futile.