Early mortality of stage IV non-small cell lung cancer in the United States

Early mortality in German patients with lung cancer: risk factors associated with 30-and 60-day mortality

Despite therapeutic advances, early mortality in lung cancer is still prevalent. In this study, we aimed to assess risk factors for 30- and 60-day mortality in German lung cancer patients. In this retrospective cross-sectional analysis, we used data of lung cancer patients treated at LMU Hospital Munich between 2015 and 2019. We categorized patients into 30-day mortality, 60 day-mortality, and longer survival. We used Student's t-test and ANOVA to compare means and Chi2-test to compare frequencies. We used logistic regression analysis to identify factors associated with a risk for early mortality. Of the 2454 lung cancer patients, 2.0% (n = 50) died within 30 and 1.7% (n = 41) within 30 to 60 days of diagnosis. Older age and advanced stage at diagnosis were significantly associated with early mortality in the univariate and the multivariate analysis. Patients in the 30-day mortality group significantly more often did not receive tumor-directed therapy. They were also more likely to die in an acute care setting compared to the 60-day mortality group. The group of patients who died unexpectedly (12.0%) was dominantly female, with a high proportion of patients with unintentional weight loss at the time of diagnosis. Our results suggest that in the treatment of patients with lung cancer there is a need for a greater focus on older patients. Moreover, physicians should pay special attention to females with recent weight loss and patients with a comorbidity of diabetes mellitus or renal impairment. Engaging a case manager focused on detecting patients with the above characteristics could help improve overall care.

Early death after a diagnosis of metastatic solid cancer-raising awareness and identifying risk factors from the SEER database

BACKGROUND

Cancer death rates are declining, in part due to smoking cessation, better detection and new treatments; nevertheless, a large fraction of metastatic cancer patients die soon after diagnosis. Few studies and interventions focus on these patients. Our study aims to characterize early mortality in a wide range of metastatic solid tumors.

METHODS

We retrieved data on adult patients diagnosed with pathologically confirmed de- novo metastatic solid tumors between the years 2004-2016 from the Surveillance, Epidemiology, and End Results database (SEER). Our primary outcome was cancer specific early death rate (defined as death within two months of diagnosis). Additional data extracted included socio-demographical data, tumor primary, sites of metastases, and cause of death.

RESULTS

109,207 (20.8%) patients died of de-novo metastatic cancer within two months of diagnosis. The highest rates of early death were found in hepatic (36%), pancreato-biliary (31%) and lung (25%) primaries. Factors associated with early death included primary site, liver, and brain metastases, increasing age, and lower income. Cancer was the cause of death in 92.1% of all early deaths. Two-month mortality rates have moderately improved during the study period (from 22.4% in 2004 to 18.8% in 2016).

CONCLUSION

A fifth of de-novo metastatic cancer patients die soon after diagnosis, with little improvement over the last decade. Further research is required to better classify and identify patients at risk for early mortality, which patients might benefit from faster diagnostic tracks, and which might avoid invasive and futile diagnostic procedures.

Thirty-day mortality in hospitalised patients with lung cancer: incidence and predictors

OBJECTIVES

Patients with lung cancer experience high rates of hospitalisation, mainly due to the high risk of complications that emerge during the natural history of the disease. We designed a retrospective, single-centre, observational study aimed at defining the clinical predictors of 30-day mortality in hospitalised patients with lung cancer.

METHODS

Clinical records from the first admission of patients with lung cancer to the oncology ward of the University Hospital of Parma from 1 January 2017 to 1 January 2022 were collected.

RESULTS

251 consecutive patients were enrolled at the time of data cut-off. In the univariate analysis, baseline clinical predictors of 30-day mortality were Eastern Cooperative Oncology Group performance status (ECOG PS) (≥2 vs 0-1: 27.5% vs 14.8%, p=0.028), high Blaylock Risk Assessment Screening Score (BRASS) (high vs intermediate-low: 34.3% vs 11.9%, p<0.001), presence of pain (yes vs no: 24.4% vs 11.7%, p=0.009), number of metastatic sites (≥3 vs <3: 26.5% vs 13.4%, p=0.017) and presence of bone metastases (yes vs no: 29.0% vs 10.8%, p=0.001). In the multivariate analysis, high BRASS remained significantly associated with increased 30-day mortality (high vs intermediate-low; OR 2.87, 95% CI 1.21 to 6.78, p=0.016).

CONCLUSION

Our results suggest that baseline poor ECOG PS, high BRASS, presence of pain, high tumour burden and presence of bone metastases could be used as clinical predictors of 30-day mortality in hospitalised patients with lung cancer. In particular, the BRASS scale should be used as a simple tool to predict 30-day mortality in hospitalised patients with lung cancer.

Risk factors for early mortality of lung cancer patients in France: A nationwide analysis

BACKGROUND

Despite therapeutic advances, lung cancer remains the first cause of death from cancer. The main objective of this study was to identify risk factors associated with death within 3-months of the first hospitalization for lung cancer in France.

METHODS

This analysis included patients with a first hospitalization for lung cancer (between January 1, 2016 and December 31, 2018) according to diagnosis-related groups entered into the French national medical-administrative database. Clinical and socioeconomic parameters and characteristics of that first hospitalization were analyzed. A model predictive of early mortality was developed based on those variables.

RESULTS

The 144,087 included patients were 67% men; median age of 68 [interquartile range 60-76] years; 47% had metastatic disease at diagnosis; and 34% and 23%, respectively, had received systemic treatment or undergone curative surgery. The 3-month mortality was 19%, and significantly higher for those ≥70 versus <70 years old (OR 1.33, 1.22-1.45), men versus. women (OR 1.50, 1.44-1.55), those with metastatic disease at diagnosis (OR, 3.30, 3.18-3.43), first hospitalization via the emergency room (OR 1.65 1.59-1.71) and first hospitalization lasting >30 days (OR, 1.58 1.49-1.68). In contrast, no socioeconomic characteristic was associated with early mortality.

CONCLUSION

Almost 1 in 5 patients diagnosed with lung cancer in France died within 3 months post-diagnosis. Improving survival requires diagnosis at an earlier stage and better organization of diagnosis and specific care pathways.

Factors associated with early lung cancer mortality: a systematic review

Introduction: Despite recent therapeutic advances, lung cancer remains the primary cause of cancer deaths worldwide, and early lung mortality was poorly studied.Area covered: Early lung-cancer mortality reflects local therapy (surgery or radiotherapy) impact (localized forms), and metastatic disease evolution, comorbidities and healthcare-system accessibility. The definition of early lung cancer mortality is not consensual; thresholds range from 1 to 12 months post-diagnosis. This systematic review was undertaken to identify and analyze factors significantly associated with early lung cancer mortality. Age, male sex, non-adenocarcinoma histology, advanced stage at diagnosis and ECOG performance status are the main clinical factors of early lung cancer mortality. Active/ex-smoking also seems to favor early mortality, despite heterogeneous definitions of smoker status. For radio-chemotherapy treated locally advance disease, the early mortality rate increases according to tumor volume. Less well studied, socioeconomic characteristics (rurality and social deprivation index) yielded contradictory results, partially because definitions vary over studies. However, early lung cancer mortality is significantly higher for lower socioeconomic class patients.Expert opinion: Prospective, observational, general population studies are needed to better evaluate early lung-cancer mortality. International consensus concerning the patient-, disease- or healthcare system-linked factors of interest to be collected would facilitate comparisons among countries.

AKIP1 expression in tumor tissue as a new biomarker for disease monitoring and prognosis in non-small cell lung cancer: Results of a retrospective study

Background

A‐kinase–interacting protein 1 (AKIP1) has been reported as an oncogenetic factor in multiple cancers; however, no study has reported its role in non‐small cell lung cancer (NSCLC) yet. This study aimed to evaluate the expression of AKIP1, and its correlation with tumor characteristics as well as prognosis in patients with NSCLC.

Methods

Four hundred and ninety patients with NSCLC who underwent resection were reviewed, and baseline clinical data were collected. AKIP1 expression in tumor tissue/paired adjacent tissue was detected by immunohistochemistry. Disease‐free survival (DFS) and overall survival (OS) were calculated.

Results

A‐kinase–interacting protein 1 expression was elevated in tumor tissue compared with paired adjacent tissue (P < .001), and high AKIP1 tumor tissue expression was correlated with poor pathological differentiation (P < .001), tumor size >5 cm (P = .001), lymph node metastasis (P = .016), higher TNM stages (P < .001), and abnormal CEA level (>5 ng/mL) (P = .035). DFS was worse in patients with tumor tissue AKIP1 high expression compared with patients who had AKIP1 low expression in total patients (P < .001), TNM stage I (P < .001) and TNM stage III (P < .001) patients. And the OS was also decreased in patients with AKIP1 high expression in total patients (P < .001), TNM stage I patients (P = .001) and TNM stage III patients (P = .004). Moreover, multivariate Cox's proportional hazards regression model analysis revealed that AKIP1 high expression was an independent predictive factor for worse DFS (P < .001) and OS (P < .001).

Conclusion

Tumor tissue AKIP1 expression may have the potential to be a biomarker assisting in disease monitoring and prognosis in NSCLC.