Variable impact of prior cancer history on the survival of lung cancer patients

Impact of prior cancer history on the prognosis of extranodal NK/T-cell lymphoma

Our goal was to assess the impact of prior cancer history on the prognosis of extranodal NK/T-cell lymphoma (ENKTCL). We searched the SEER database to retrospectively enroll patients with ENKTCL. The effects of cancer history on overall survival (OS) and disease-specific survival (DSS) were analyzed using the Cox model. A total of 691 patients were included, of whom 54 (7.8%) had prior histories of cancer. The most common solid malignancy was bone/soft tissue sarcoma. Most secondary ENKTCL cases occurred within 5-9 years following the first cancer diagnosis. Radiotherapy and chemotherapy had been administered to 45 and 40 patients, respectively, to treat their previous malignancies. Prior cancer history had little impact on DSS; however, the presence of prior solid cancer history, latency period of 10+ years, and prior administration of radiotherapy or chemotherapy significantly decreased OS. Prior cancer history had no effect on DSS, but survival compromised OS under specific circumstances.

Racial and Ethnic Disparities in Survival Among People With Second Primary Cancer in the US

Importance

Comprehensive data for racial and ethnic disparities after second primary cancers (SPCs) are lacking despite the growing burden of SPCs.

Objective

To quantify racial and ethnic disparities in survival among persons with SPCs.

Design, Setting, and Participants

This population-based, retrospective cohort study used data from 18 Surveillance, Epidemiology, and End Results registries in the US for persons diagnosed with the most common SPCs at age 20 years or older from January 1, 2000, to December 31, 2013 (with follow-up through December 31, 2018). Data were analyzed between January and April 2023.

Exposure

Race and ethnicity (Hispanic, non-Hispanic Asian or Pacific Islander, non-Hispanic Black, and non-Hispanic White).

Main Outcomes and Measures

The main outcomes were 5-year relative survival and cause-specific survival. Cause-specific hazard ratios (HRs) were calculated for death from cancer or cardiovascular disease (CVD) in each racial and ethnic minority population compared with the White population overall and stratified by SPC type, with adjustment for sex, year and age at SPC diagnosis, and prior cancer type and stage (baseline model) and additionally for county attributes (household income, urbanicity), SPC characteristics (stage, subtype), and treatment.

Results

Among 230 370 persons with SPCs (58.4% male), 4.5% were Asian or Pacific Islander, 9.6% were Black, 6.4% were Hispanic, and 79.5% were White. A total of 109 757 cancer-related deaths (47.6%) and 18 283 CVD-related deaths (7.9%) occurred during a median follow-up of 54 months (IQR, 12-93 months). In baseline models, compared with the White population, the risk of cancer-related death overall was higher in the Black (HR, 1.21; 95% CI, 1.18-1.23) and Hispanic (HR, 1.10; 95% CI, 1.07-1.13) populations but lower in the Asian or Pacific Islander population (HR, 0.93; 95% CI, 0.90-0.96). When stratified by 13 SPC types, the risk of cancer-related death was higher for 10 SPCs in the Black population, with the highest HR for uterine cancer (HR, 1.87; 95% CI, 1.63-2.15), and for 7 SPCs in the Hispanic population, most notably for melanoma (HR, 1.46; 95% CI, 1.21-1.76). For CVD-related death, the overall HR was higher in the Black population (HR, 1.41; 95% CI, 1.34-1.49), with elevated risks evident for 11 SPCs, but lower in the Asian or Pacific Islander (HR, 0.75; 95% CI, 0.69-0.81) and Hispanic (HR, 0.90; 95% CI, 0.84-0.96) populations than in the White population. After further adjustments for county attributes and SPC characteristics and treatment, HRs were reduced for cancer-related death and for CVD-related death and associations in the same direction remained.

Conclusions and Relevance

In this cohort study of SPC survivors, the Black population had the highest risk of both death from cancer and death from CVD, and the Hispanic population had a higher risk of death from cancer than the White population. Attenuations in HRs after adjustment for potentially modifiable factors highlight opportunities to reduce survival disparities among persons with multiple primary cancers.

Survival in non-small cell lung cancer patients with versus without prior cancer

Clinical trials on cancer treatments frequently exclude patients with prior cancer, but more evidence is needed to understand their possible effects on outcomes. This study analyzed the prognostic impact of prior cancer in newly diagnosed non-small cell lung cancer (NSCLC) patients while accounting for various patient and cancer characteristics. Using population-based cancer registry data linked with administrative claims data, this retrospective cohort study examined patients aged 15-84 years diagnosed with NSCLC between 2010 and 2015 in Japan. Cox proportional hazards models were used to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs) of all-cause mortality in patients with versus without prior cancer. The analysis was stratified according to NSCLC stage and diagnostic time intervals between prior cancers and the index NSCLC. We analyzed 9103 patients (prior cancer: 1416 [15.6%]; no prior cancer: 7687 [84.4%]). Overall, prior cancer had a non-significant mortality HR of 1.07 (95% CI: 0.97-1.17). Furthermore, prior cancer had a significantly higher mortality hazard for diagnostic time intervals of 3 years (HR: 1.23, 95% CI: 1.06-1.43) and 5 years (1.18, 1.04-1.33), but not for longer intervals. However, prior cancer in patients with more advanced NSCLC did not show a higher mortality risk for any diagnostic time interval. Smoking-related prior cancers and prior cancers with poorer prognosis were associated with poorer survival. NSCLC patients with prior cancer do not have an invariably higher risk of mortality, and should be considered for inclusion in clinical trials depending on their cancer stage.

Impact of Prior Cancer History on Outcomes of Resected Lung Cancer

BACKGROUND

Previous studies concerning the impact of prior cancer on newly diagnosed lung cancer are mainly based on databases and obtained mixed results. Utilizing a large study population, we aimed to reveal this impact.

PATIENTS AND METHODS

Lung cancer patients from January 2008 to April 2021 were enrolled. The Kaplan-Meier method was used to perform survival analyses. To investigate the impact of prior cancer, a Cox proportional hazards model was conducted. To minimize the influence of the heterogeneity of prior cancer, stratified analyses were carried out.

RESULTS

In total, 17,423 lung cancer patients were reviewed, among which we identified 1469 (8.4%) patients with a history of prior cancer. Cox regression analysis revealed that prior cancer was an independent poor prognostic factor on overall survival (HR = 1.430, 95% CI: 1.147-1.784, p = 0.001) but did not affect lung cancer-specific survival (HR = 1.120, 95% CI: 0.876-1.434, p = 0.366). Interestingly, in further stratified analyses, we found that prior cancer history affected overall survival only in pTNM stage 0/I patients (HR = 1.670, 95% CI: 1.247-2.237, p = 0.001), but not in pTNM stage II/III/IV patients (HR = 1.237, 95% CI: 0.877-1.743, p = 0.226). Similarly, prior cancer was an independent poor prognostic factor on overall survival only for pN0 patients. Subsequently, subgroup analyses indicated that the impact of prior cancer varied in pTNM stage 0/I patients according to the type of prior cancer and the interval time.

CONCLUSIONS

Considering that prior cancer affects overall survival in patients with clinically curable lung cancer, clinicians should pay attention to this effect and improve the management of these patients to achieve a better prognosis.

Is prior cancer history a hindrance for non-small cell lung cancer patients to participate in clinical trials?

BACKGROUND

This study aimed to explore the effect of a prior cancer history on the survivals of resected non-small cell lung cancer (NSCLC) patients.

METHODS

Kaplan-Meier method with a log-rank test was used to compare overall survival (OS) and disease-free survival (DFS) between groups. Propensity score matching (PSM) method was used to reduce bias. The least absolute shrinkage and selection operator (LASSO)-penalized Cox multivariable analysis was used to identify the prognostic factors.

RESULTS

A total of 4,102 eligible cases were included in this study. The rate of patients with a prior cancer was 8.2% (338/4,102). Patients with a prior cancer tended to be younger and have early-stage tumors when compared with those without prior cancer. Before PSM, the survivals of the patients with a prior cancer were similar to those of the patients without prior cancer (OS: P = 0.591; DFS: P = 0.847). After PSM, patients with a prior cancer and those without prior cancer still had comparable survival rates (OS: P = 0.126; DFS: P = 0.054). The LASSO-penalized multivariable Cox analysis further confirmed that a prior cancer history was not a prognostic factor for both OS and DFS.

CONCLUSIONS

A prior cancer history was not associated with resected NSCLC patients' survivals, and we proposed that it might be reasonable for clinical trials to enroll the NSCLC patients with a prior cancer.

Understanding the Implications of Medicaid Expansion for Cancer Care in the US: A Review

Importance

Insurance status has been linked to important differences in cancer treatment and outcomes in the US. With more than 15 million individuals gaining health insurance through Medicaid expansion, there is an increasing need to understand the implications of this policy within the US cancer population. This review provides an overview of the fundamental principles and nuances of Medicaid expansion, as well as the implications for cancer care.

Observations

The Patient Protection and Affordable Care Act presented states with an option to expand Medicaid coverage by broadening the eligibility criteria (eg, raising the eligible income level). During the past 10 years, Medicaid expansion has been credited with a 30% reduction in the population of uninsured individuals in the US. Such a significant change in the insurance profile could have important implications for the 1.7 million patients diagnosed with cancer each year, the oncology teams that care for them, and policy makers. However, several factors may complicate efforts to characterize the effect of Medicaid expansion on the US cancer population. Most notably, there is considerable variation among states in terms of whether Medicaid expansion took place, when expansion occurred, eligibility criteria for Medicaid, and coverage types that Medicaid provides. In addition, economic and health policy factors may be intertwined with factors associated with Medicaid expansion. Finally, variability in the manner in which cancer care has been captured and depicted in large databases could affect the interpretation of findings associated with expansion.

Conclusions and Relevance

The expansion of Medicaid was a historic public policy initiative. To fully leverage this policy to improve oncological care and to maximize learning for subsequent policies, it is critical to understand the effect of Medicaid expansion. This review aims to better prepare investigators and their audiences to fully understand the implications of this important health policy initiative.

Survival analysis of patients with primary breast duct carcinoma and lung adenocarcinoma: a population-based study from SEER

The appeal to enroll patients with primary breast and lung cancer in clinical trials is increasing, but survival of these two primary cancers remains to be elucidated. This study analyzed the prognosis of primary breast duct carcinoma with subsequent lung adenocarcinoma (BCLA) and primary breast duct carcinoma with prior lung adenocarcinoma (LABC). Cohorts of 3,515 patients with BCLA and 654 patients with LABC were identified from the Surveillance, Epidemiology, and End Results database. Patients were classified into simultaneous two primary cancer (sTPC), metachronous two primary cancer (mTPC1), or mTPC2 groups when the interval times between breast and lung cancer were within 6 months, between 7 and 60 months, or over 60 months, respectively. The propensity score matching program (PSM) was applied to determine the survival of BCLA/LABC relative to single breast/lung cancer. Cox proportional hazard regression model and competing risk modes were performed to identify confounders associated with all-cause and cancer-specific death, respectively. Survival of patients with LABC/BCLA relative to single breast/lung cancer was accessed via median survival time. The survival of patients with BCLA/LABC was generally poor compared with the survival of those with single breast cancer. The PSM-estimated HR in the sTPC group with BCLA and in the mTPC1 and mTPC2 groups with LABC were 0.75 (95% CI 0.62–0.90), 0.52 (95% CI 0.27–0.98), and 0.36 (95% CI 0.20–0.65), respectively, whereas the SHRs were 0.80 (95% CI 0.66–0.97), 0.68 (95% CI 0.34–1.34), and 0.46 (95% CI 0.27–0.80), respectively, compared with those in the single lung cancer group. By contrast, the survival rates of the remaining patients did not differ. The median survival times since secondary malignancy were 42, 23, and 20 months in the sTPC, mTPC1, and mTPC2 groups with BCLA, respectively, and 18, 60, and 180 months in those with LABC, respectively. For patients with BCLA, the adjusted Cox regression suggested incidences of all-cause deaths in mTPC1group were statically higher than those in sTPC group, whereas the incidences of all-cause and cancer-specific death in the mTPC1 and mTPC2 groups were statistically lower than those in the sTPC group. The prognosis of patients with breast cancer and subsequent lung cancer of over 18 months was not significantly different than that of single lung cancer, which supported the profound appeal to increase the involvement of these two primary cancers in potential beneficial clinical trials. For patients with lung cancer and prior breast cancer of within 6 months and subsequent breast cancer of over 18 months, prognosis was improved relative to single lung cancer. Therefore, additional attention is needed to eliminate the potential bias may when these patients are recruited in the clinical trials.

Lung Cancer Screening With Low Dose Computed Tomography in Patients With and Without Prior History of Cancer in the National Lung Screening Trial

INTRODUCTION

Patients with a prior history of cancer (PHC) are at increased risk of second primary malignancy, of which lung cancer is the most common. We compared the performance metrics of positive screening rates and cancer detection rates (CDRs) among those with versus without PHC.

METHODS

We conducted a secondary analysis of 26,366 National Lung Screening Trial participants screened with low dose computed tomography between August 2002 and September 2007. We evaluated absolute rates and age-adjusted relative risks (RRs) of positive screening rates on the basis of retrospective Lung CT Screening Reporting & Data System (Lung-RADS) application, invasive diagnostic procedure rate, complication rate, and CDR in those with versus without PHC using a binary logistic regression model using Firth's penalized likelihood. We also compared cancer type, stage, and treatment in those with versus without PHC.

RESULTS

A total of 4.1% (n = 1071) of patients had PHC. Age-adjusted rates of positive findings were similar in those with versus without PHC (Baseline: PHC = 13.7% versus no PHC = 13.3%, RR [95% confidence interval (CI)]: 1.04 [0.88-1.24]; Subsequent: PHC = 5.6% versus no PHC = 5.5%, RR [95% CI]: 1.02 [0.84-1.23]). Age-adjusted CDRs were higher in those with versus without PHC on baseline (PHC=1.9% versus no PHC = 0.8%, RR [95% CI]: 2.51 [1.67-3.81]) but not on subsequent screenings (PHC = 0.6% versus no PHC = 0.4%, RR [95% CI]: 1.37 [0.99-1.93]). There were no differences in cancer stage, type, or treatment by PHC status.

CONCLUSIONS

Patients with PHC may benefit from lung cancer screening, and with their providers, should be made aware of the possibility of higher cancer detection, invasive procedures, and complication rates on baseline lung cancer screening, but not on subsequent low dose computed tomography screening examinations.

Survival After Cancer Treatment at Top-Ranked US Cancer Hospitals vs Affiliates of Top-Ranked Cancer Hospitals

IMPORTANCE

Hospital networks formed around top-ranked cancer hospitals represent an opportunity to optimize complex cancer care in the community.

OBJECTIVE

To compare the short- and long-term survival after complex cancer treatment at top-ranked cancer hospitals and the affiliates of top-ranked hospitals.

DESIGN, SETTING, AND PARTICIPANTS

This cohort study was conducted using data from the unabridged version of the National Cancer Database. Included patients were individuals 18 years or older who underwent surgical treatment for esophageal, gastric, lung, pancreatic, colorectal, or bladder cancer diagnosed between January 1, 2012, and December 31, 2016. Patient outcomes after complex surgical procedures for cancer at top-ranked cancer hospitals (as ranked in top 50 by US News and World Report) were compared with outcomes at affiliates of top-ranked cancer hospitals (affiliation listed in American Hospitals Association survey and confirmed by search of internet presence). Data were analyzed from July through December 2019.

EXPOSURES

Undergoing complex cancer treatment at a top-ranked cancer hospital or an affiliated hospital.

MAIN OUTCOMES AND MEASURES

The association of affiliate status with short-term survival (ie, 90-day mortality) was compared using logistic regression, and the association of affiliate status with long-term survival was compared using time-to-event models, adjusting for patient demographic, payer, clinical, and treatment factors.

RESULTS

Among 119 834 patients who underwent surgical treatment for cancer, 79 981 patients (66.7%) were treated at top-ranked cancer hospitals (median [interquartile range] age, 66 [58-74] years; 40 910 [54.9%] men) and 39 853 patients (33.3%) were treated at affiliate hospitals (median [interquartile range] age, 69 [60-77] years; 19 004 [50.0%] men). In a pooled analysis of all cancer types, adjusted perioperative mortality within 90 days of surgical treatment was higher at affiliate hospitals compared with top-ranked hospitals (odds ratio, 1.67 [95% CI, 1.49-1.89]; P < .001). Adjusted long-term survival following cancer treatment at affiliate hospitals was only 77% that of top-ranked hospitals (time ratio, 0.77 [95% CI, 0.72-0.83]; P < .001). The survival advantage was not fully explained by differences in annual surgical volume, with both long- and short-term survival remaining superior at top-ranked hospitals even after models were adjusted for volume.

CONCLUSIONS AND RELEVANCE

These findings suggest that short- and long-term survival after complex cancer treatment were superior at top-ranked hospitals compared with affiliates of top-ranked hospitals. Further study of cancer care within top-ranked cancer networks could reveal collaborative opportunities to improve survival across a broad contingent of the US population.

Mortality for Robotic- vs Video-Assisted Lobectomy-Treated Stage I Non-Small Cell Lung Cancer Patients

Background

To address the US Food and Drug Administration’s recent safety concern on robotic surgery procedures, we compared short- and long-term mortality for stage I non-small cell lung cancer (NSCLC) patients treated by robotic-assisted thoracoscopic surgical lobectomy (RATS-L) vs video-assisted thoracoscopic surgical lobectomy (VATS-L).

Methods

From the National Cancer Database, we identified 18 908 stage I NSCLC patients who underwent RATS-L or VATS-L as the primary operation from 2010 to 2014. Cox proportional hazards models were used to estimate hazard ratios (HRs) for short- and long-term mortality using unmatched and propensity score–matched analyses. All statistical tests were 2-sided.

Results

Patients treated by RATS-L had higher 90-day mortality than those with VATS-L (6.6% vs 3.8%, P = .03) if conversion to open thoracotomy occurred. After excluding first-year observation, multiple regression analyses showed RATS-L was associated with increased long-term mortality, compared with VATS-L, in cases with tumor size 20 mm or less: hazard ratio (HR) = 1.33 (95% confidence interval [CI] = 1.15 to 1.55), HR = 1.36 (95% CI = 1.17 to 1.58), and HR = 1.33 (95% CI = 1.11 to 1.61) for unmatched, N:1 matched, and 1:1 matched analyses, respectively, in the intention-to-treat analysis. Among patients without conversion to an open thoracotomy, the respective hazard ratios were 1.19 (95% CI = 1.10 to 1.29), 1.19 (95% CI = 1.10 to 1.29), and 1.17 (95% CI = 1.06 to 1.29). Similar associations were observed when follow-up time started 18 or 24 months postsurgery. No statistically significant mortality difference was found for patients with tumor size of greater than 20 mm. These associations were not related to case volume of VATS-L or RATS-L performed at treatment institutes.

Conclusions

Patients with small (≤20 mm) stage I NSCLC treated with RATS-L had statistically significantly higher long-term mortality risk than VATS-L after 1 year postsurgery.