Smoking and the Risk of Second Primary Lung Cancer Among Breast Cancer Survivors from the Population-Based UK Biobank Study

OBJECTIVE

Long-term breast cancer (BC) survivors are known to develop second malignancies, with second primary lung cancer (SPLC) one common type. Smoking was identified as a main risk factor for SPLC among BC survivors. These findings were limited to the U.S. and focused on smoking status, not incorporating cumulative smoking exposures (eg, pack-years). We examine SPLC incidence and evaluate the associations between SPLC risk and cumulative cigarette smoking exposures and other potential factors among BC survivors in a prospective European cohort.

METHODS

Of 502,505 participants enrolled in the UK Biobank in 2006 to 2010, we identified 8429 patients diagnosed with BC between 2006 and 2016 and followed for second malignancies through 2016. Smoking information was collected at enrollment, and treatment data were collected using electronic health records. Multivariable cause-specific Cox regression (CSC) evaluated the association between each factor and SPLC risk.

RESULTS

Of 8429 BC patients, 40 (0.47%) developed SPLC over 45,376 person-years. The 10-year cumulative SPLC incidence was 0.48% (95% CI = 0.33%-0.62%). The CSC analysis confirmed the association between SPLC and ever-smoking status (adjusted hazard-ratio (aHR) = 3.46 (P < .001). The analysis showed a 24% increment in SPLC risk per 10 smoking pack-years among BC survivors (aHR = 1.24 per-10 pack-years, P = .01). The associations between SPLC and other variables remained statistically insignificant. We applied the USPSTF lung cancer screening eligibility criteria and found that 80% of the 40 BC survivors who developed SPLC would have been ineligible for lung cancer screening.

CONCLUSION

In a large, European cohort, cumulative smoking exposure is significantly associated with SPLC risk among BC survivors.

Racial and ethnic differences in second primary lung cancer risk among lung cancer survivors

BACKGROUND

Recent therapeutic advances have improved survival among lung cancer (LC) patients, who are now at high risk of second primary lung cancer (SPLC). Hispanics comprise the largest minority in the United States, who have shown a lower LC incidence and mortality than other races, and yet their SPLC risk is poorly understood. We quantified the SPLC incidence patterns among Hispanics vs other races.

METHODS

We used data from the Multiethnic Cohort, a population-based cohort of 5 races (African American, Japanese American, Hispanic, Native Hawaiian, and White), recruited between 1993 and 1996 and followed through 2017. We identified patients diagnosed with initial primary lung cancer (IPLC) and SPLC via linkage to Surveillance, Epidemiology, and End Results registries. We estimated the 10-year cumulative incidence of IPLC (in the entire cohort) and SPLC (among IPLC patients). A standardized incidence ratio (SIR) was calculated as the ratio of SPLC-to-IPLC incidence by race and ethnicity.

RESULTS

Among 202 692 participants, 6788 (3.3%) developed IPLC over 3 871  417 person-years. The 10-year cumulative IPLC incidence was lower among Hispanics (0.80%, 0.72 to 0.88) vs Whites (1.67%, 1.56 to 1.78) or Blacks (2.44%, 2.28 to 2.60). However, the 10-year SPLC incidence following IPLC was higher among Hispanics (3.11%, 1.62 to 4.61) vs Whites (2.80%, 1.94 to 3.66) or Blacks (2.29%, 1.48 to 3.10), resulting in a significantly higher SIR for Hispanics (SIR = 8.27, 5.05 to 12.78) vs Whites (SIR = 5.60, 4.11 to 7.45) or Blacks (SIR = 3.48, 2.42 to 4.84; P < .001).

CONCLUSION

Hispanics have a higher SPLC incidence following IPLC than other races, which may be potentially due to better survival after IPLC and extended duration for SPLC development. Continuing surveillance is warranted to reduce racial disparities among LC survivors.

Risk model-based management for second primary lung cancer among lung cancer survivors through a validated risk prediction model

BACKGROUND

Recent therapeutic advances and screening technologies have improved survival among patients with lung cancer, who are now at high risk of developing second primary lung cancer (SPLC). Recently, an SPLC risk-prediction model (called SPLC-RAT) was developed and validated using data from population-based epidemiological cohorts and clinical trials, but real-world validation has been lacking. The predictive performance of SPLC-RAT was evaluated in a hospital-based cohort of lung cancer survivors.

METHODS

The authors analyzed data from 8448 ever-smoking patients diagnosed with initial primary lung cancer (IPLC) in 1997-2006 at Mayo Clinic, with each patient followed for SPLC through 2018. The predictive performance of SPLC-RAT and further explored the potential of improving SPLC detection through risk model-based surveillance using SPLC-RAT versus existing clinical surveillance guidelines.

RESULTS

Of 8448 IPLC patients, 483 (5.7%) developed SPLC over 26,470 person-years. The application of SPLC-RAT showed high discrimination area under the receiver operating characteristics curve: 0.81). When the cohort was stratified by a 10-year risk threshold of ≥5.6% (i.e., 80th percentile from the SPLC-RAT development cohort), the observed SPLC incidence was significantly elevated in the high-risk versus low-risk subgroup (13.1% vs. 1.1%, p < 1 × 10-6 ). The risk-based surveillance through SPLC-RAT (≥5.6% threshold) outperformed the National Comprehensive Cancer Network guidelines with higher sensitivity (86.4% vs. 79.4%) and specificity (38.9% vs. 30.4%) and required 20% fewer computed tomography follow-ups needed to detect one SPLC (162 vs. 202).

CONCLUSION

In a large, hospital-based cohort, the authors validated the predictive performance of SPLC-RAT in identifying high-risk survivors of SPLC and showed its potential to improve SPLC detection through risk-based surveillance.

PLAIN LANGUAGE SUMMARY

Lung cancer survivors have a high risk of developing second primary lung cancer (SPLC). However, no evidence-based guidelines for SPLC surveillance are available for lung cancer survivors. Recently, an SPLC risk-prediction model was developed and validated using data from population-based epidemiological cohorts and clinical trials, but real-world validation has been lacking. Using a large, real-world cohort of lung cancer survivors, we showed the high predictive accuracy and risk-stratification ability of the SPLC risk-prediction model. Furthermore, we demonstrated the potential to enhance efficiency in detecting SPLC using risk model-based surveillance strategies compared to the existing consensus-based clinical guidelines, including the National Comprehensive Cancer Network.

Software Application Profile: dynamicLM-a tool for performing dynamic risk prediction using a landmark supermodel for survival data under competing risks

MOTIVATION

Providing a dynamic assessment of prognosis is essential for improved personalized medicine. The landmark model for survival data provides a potentially powerful solution to the dynamic prediction of disease progression. However, a general framework and a flexible implementation of the model that incorporates various outcomes, such as competing events, have been lacking. We present an R package, dynamicLM, a user-friendly tool for the landmark model for the dynamic prediction of survival data under competing risks, which includes various functions for data preparation, model development, prediction and evaluation of predictive performance.

IMPLEMENTATION

dynamicLM as an R package.

GENERAL FEATURES

The package includes options for incorporating time-varying covariates, capturing time-dependent effects of predictors and fitting a cause-specific landmark model for time-to-event data with or without competing risks. Tools for evaluating the prediction performance include time-dependent area under the ROC curve, Brier Score and calibration.

AVAILABILITY

Available on GitHub [https://github.com/thehanlab/dynamicLM].

Risk Model-Based Lung Cancer Screening and Racial and Ethnic Disparities in the US

Importance

The revised 2021 US Preventive Services Task Force (USPSTF) guidelines for lung cancer screening have been shown to reduce disparities in screening eligibility and performance between African American and White individuals vs the 2013 guidelines. However, potential disparities across other racial and ethnic groups in the US remain unknown. Risk model-based screening may reduce racial and ethnic disparities and improve screening performance, but neither validation of key risk prediction models nor their screening performance has been examined by race and ethnicity.

Objective

To validate and recalibrate the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial 2012 (PLCOm2012) model-a well-established risk prediction model based on a predominantly White population-across races and ethnicities in the US and evaluate racial and ethnic disparities and screening performance through risk-based screening using PLCOm2012 vs the USPSTF 2021 criteria.

Design, Setting, and Participants

In a population-based cohort design, the Multiethnic Cohort Study enrolled participants in 1993-1996, followed up through December 31, 2018. Data analysis was conducted from April 1, 2022, to May 19. 2023. A total of 105 261 adults with a smoking history were included.

Exposures

The 6-year lung cancer risk was calculated through recalibrated PLCOm2012 (ie, PLCOm2012-Update) and screening eligibility based on a 6-year risk threshold greater than or equal to 1.3%, yielding similar eligibility as the USPSTF 2021 guidelines.

Outcomes

Predictive accuracy, screening eligibility-incidence (E-I) ratio (ie, ratio of the number of eligible to incident cases), and screening performance (sensitivity, specificity, and number needed to screen to detect 1 lung cancer).

Results

Of 105 261 participants (60 011 [57.0%] men; mean [SD] age, 59.8 [8.7] years), consisting of 19 258 (18.3%) African American, 27 227 (25.9%) Japanese American, 21 383 (20.3%) Latino, 8368 (7.9%) Native Hawaiian/Other Pacific Islander, and 29 025 (27.6%) White individuals, 1464 (1.4%) developed lung cancer within 6 years from enrollment. The PLCOm2012-Update showed good predictive accuracy across races and ethnicities (area under the curve, 0.72-0.82). The USPSTF 2021 criteria yielded a large disparity among African American individuals, whose E-I ratio was 53% lower vs White individuals (E-I ratio: 9.5 vs 20.3; P < .001). Under the risk-based screening (PLCOm2012-Update 6-year risk ≥1.3%), the disparity between African American and White individuals was substantially reduced (E-I ratio: 15.9 vs 18.4; P < .001), with minimal disparities observed in persons of other minoritized groups, including Japanese American, Latino, and Native Hawaiian/Other Pacific Islander. Risk-based screening yielded superior overall and race and ethnicity-specific performance to the USPSTF 2021 criteria, with higher overall sensitivity (67.2% vs 57.7%) and lower number needed to screen (26 vs 30) at similar specificity (76.6%).

Conclusions

The findings of this cohort study suggest that risk-based lung cancer screening can reduce racial and ethnic disparities and improve screening performance across races and ethnicities vs the USPSTF 2021 criteria.

Second Primary Lung Cancer Among Lung Cancer Survivors Who Never Smoked

Importance

Lung cancer among never-smokers accounts for 25% of all lung cancers in the US; recent therapeutic advances have improved survival among patients with initial primary lung cancer (IPLC), who are now at high risk of developing second primary lung cancer (SPLC). As smoking rates continue to decline in the US, it is critical to examine more closely the epidemiology of lung cancer among patients who never smoked, including their risk for SPLC.

Objective

To estimate and compare the cumulative SPLC incidence among lung cancer survivors who have never smoked vs those who have ever smoked.

Design, Setting, and Participants

This population-based prospective cohort study used data from the Multiethnic Cohort Study (MEC), which enrolled participants between April 18, 1993, and December 31, 1996, with follow-up through July 1, 2017. Eligible individuals for this study were aged 45 to 75 years and had complete smoking data at baseline. These participants were followed up for IPLC and further SPLC development through the Surveillance, Epidemiology, and End Results registry. The data were analyzed from July 1, 2022, to January 31, 2023.

Exposures

Never-smoking vs ever-smoking exposure at MEC enrollment.

Main Outcomes and Measures

The study had 2 primary outcomes: (1) 10-year cumulative incidence of IPLC in the entire study cohort and 10-year cumulative incidence of SPLC among patients with IPLC and (2) standardized incidence ratio (SIR) (calculated as the SPLC incidence divided by the IPLC incidence) by smoking history.

Results

Among 211 414 MEC participants, 7161 (3.96%) developed IPLC over 4 038 007 person-years, and 163 (2.28%) developed SPLC over 16 470 person-years. Of the participants with IPLC, the mean (SD) age at cohort enrollment was 63.6 (7.7) years, 4031 (56.3%) were male, and 3131 (43.7%) were female. The 10-year cumulative IPLC incidence was 2.40% (95% CI, 2.31%-2.49%) among ever-smokers, which was 7 times higher than never-smokers (0.34%; 95% CI, 0.30%-0.37%). However, the 10-year cumulative SPLC incidence following IPLC was as high among never-smokers (2.84%; 95% CI, 1.50%-4.18%) as ever-smokers (2.72%; 95% CI, 2.24%-3.20%), which led to a substantially higher SIR for never-smokers (14.50; 95% CI, 8.73-22.65) vs ever-smokers (3.50; 95% CI, 2.95-4.12).

Conclusions and Relevance

The findings indicate that SPLC risk among lung cancer survivors who never smoked is as high as among those with IPLC who ever-smoked, highlighting the need to identify risk factors for SPLC among patients who never smoked and to develop a targeted surveillance strategy.

Overall Survival Among Patients With De Novo Stage IV Metastatic and Distant Metastatic Recurrent Non-Small Cell Lung Cancer

Importance

Despite recent breakthroughs in therapy, advanced lung cancer still poses a therapeutic challenge. The survival profile of patients with metastatic lung cancer remains poorly understood by metastatic disease type (ie, de novo stage IV vs distant recurrence).

Objective

To evaluate the association of metastatic disease type on overall survival (OS) among patients with non-small cell lung cancer (NSCLC) and to identify potential mechanisms underlying any survival difference.

Design, Setting, and Participants

Cohort study of a national US population based at a tertiary referral center in the San Francisco Bay Area using participant data from the National Lung Screening Trial (NLST) who were enrolled between 2002 and 2004 and followed up for up to 7 years as the primary cohort and patient data from Stanford Healthcare (SHC) for diagnoses between 2009 and 2019 and followed up for up to 13 years as the validation cohort. Participants from NLST with de novo metastatic or distant recurrent NSCLC diagnoses were included. Data were analyzed from January 2021 to March 2023.

Exposures

De novo stage IV vs distant recurrent metastatic disease.

Main Outcomes and Measures

OS after diagnosis of metastatic disease.

Results

The NLST and SHC cohort consisted of 660 and 180 participants, respectively (411 men [62.3%] vs 109 men [60.6%], 602 White participants [91.2%] vs 111 White participants [61.7%], and mean [SD] age of 66.8 [5.5] vs 71.4 [7.9] years at metastasis, respectively). Patients with distant recurrence showed significantly better OS than patients with de novo metastasis (adjusted hazard ratio [aHR], 0.72; 95% CI, 0.60-0.87; P < .001) in NLST, which was replicated in SHC (aHR, 0.64; 95% CI, 0.43-0.96; P = .03). In SHC, patients with de novo metastasis more frequently progressed to the bone (63 patients with de novo metastasis [52.5%] vs 19 patients with distant recurrence [31.7%]) or pleura (40 patients with de novo metastasis [33.3%] vs 8 patients with distant recurrence [13.3%]) than patients with distant recurrence and were primarily detected through symptoms (102 patients [85.0%]) as compared with posttreatment surveillance (47 patients [78.3%]) in the latter. The main finding remained consistent after further adjusting for metastasis sites and detection methods.

Conclusions and Relevance

In this cohort study, patients with distant recurrent NSCLC had significantly better OS than those with de novo disease, and the latter group was associated with characteristics that may affect overall survival. This finding can help inform future clinical trial designs to ensure a balance for baseline patient characteristics.

Abstract P055: Risk factors for second primary lung cancer among breast cancer survivors

Introduction: Breast cancer is the most common cancer in women in the U.S. As survival in breast cancer has improved, one of the key clinical problems in breast cancer survivors is the increased risk of second cancers. Over half (55%) of breast cancer survivors die from second cancers, of which lung cancer (i.e., second primary lung cancer [SPLC]) is the most frequent type. While smoking and radiotherapy have been identified as the risk factors for SPLC among breast cancer survivors, other potential factors (e.g., comorbidity, and medication) have been underexamined. In addition, women in general have shown higher susceptibility to smoking-induced lung cancer than men, suggesting the potential involvement of hormonal factors; however, the effect of hormone replacement therapy (HRT) on lung cancer risk has been controversial and has never been examined among breast cancer survivors. We aimed to examine the factors associated with SPLC risk among breast cancer survivors, focusing on the effect of HRT and its interaction with smoking. We also explored the potential of tailored risk-based management of SPLC for breast cancer survivors. Methods: We identified 5,552 patients diagnosed with breast cancer in 1993-2014 from the Prostate, Lung, Colorectal, and Ovarian Cancer (PLCO) Screening Trial. SPLC was defined as a newly diagnosed lung cancer after 6 months from the time of breast cancer diagnosis. We applied multivariable cause-specific Cox regression to identify new factors associated with SPLC risk, adjusting for multiple testing using the Bonferroni method (P&lt;0.01). We developed a prediction model to predict a 5-year risk of SPLC among breast cancer survivors that included both ever- and never-smokers and evaluated the predictive accuracy vs. a well-established lung cancer risk model, PLCOm2012, that was developed for a cancer-free population who ever smoked. Results: Of 5,552 patients, 89 (1.6%) developed SPLC over 102,545 person-years. Several factors measured at baseline in PLCO were significantly associated with SPLC risk among breast cancer survivors, including liver comorbidity (Hazard Ratio [HR] 3.28; P&lt;.001), prior history of other cancer (HR 2.02; P=0.01), and regular use of ibuprofen (HR 0.52; P=0.01). In addition, ever-use of HRT was associated with a 51% reduction in SPLC risk (HR 0.49; P=0.001). The effect of active smoking on SPLC risk vs non-active smoking (HR 7.09; P&lt;.001) was validated in PLCO. Notably, the effect of active smoking was intensified among ever-HRT users (HR=10.5; P&lt;.001) vs. never-HRT users (HR 4.1; P&lt;.001), thus showing a significant interaction (Pinteraction=0.003). The prediction model for SPLC risk was validated through bootstrap and demonstrated higher discrimination (AUC 0.83) vs. the PLCOm2012 model (AUC 0.79). Conclusions: In a large prospective cohort of breast cancer survivors, smoking and HRT use showed a significant interaction on SPLC risk. The prediction model for SPLC could identify high-risk survivors for SPLC for tailored surveillance to improve the management of breast cancer survivors.

Citation Format: Eunji Choi, Justin Lee, Julie T. Wu, Heather A. Wakelee, Lidia Schapira, Allison W. Kurian, Summer S. Han. Risk factors for second primary lung cancer among breast cancer survivors. [abstract]. In: Proceedings of the AACR Special Conference: Precision Prevention, Early Detection, and Interception of Cancer; 2022 Nov 17-19; Austin, TX. Philadelphia (PA): AACR; Can Prev Res 2023;16(1 Suppl): Abstract nr P055.

Learning through a Pandemic: The Current State of Knowledge on COVID-19 and Cancer

The ongoing coronavirus disease 2019 (COVID-19) pandemic has left patients with current or past history of cancer facing disparate consequences at every stage of the cancer trajectory. This comprehensive review offers a landscape analysis of the current state of the literature on COVID-19 and cancer, including the immune response to COVID-19, risk factors for severe disease, and impact of anticancer therapies. We also review the latest data on treatment of COVID-19 and vaccination safety and efficacy in patients with cancer, as well as the impact of the pandemic on cancer care, including the urgent need for rapid evidence generation and real-world study designs. SIGNIFICANCE: Patients with cancer have faced severe consequences at every stage of the cancer journey due to the COVID-19 pandemic. This comprehensive review offers a landscape analysis of the current state of the field regarding COVID-19 and cancer. We cover the immune response, risk factors for severe disease, and implications for vaccination in patients with cancer, as well as the impact of the COVID-19 pandemic on cancer care delivery. Overall, this review provides an in-depth summary of the key issues facing patients with cancer during this unprecedented health crisis.

Development and Validation of a Risk Prediction Tool for Second Primary Lung Cancer

Background

With advancing therapeutics, lung cancer (LC) survivors are rapidly increasing in number. Although mounting evidence suggests LC survivors have high risk of second primary lung cancer (SPLC), there is no validated prediction model available for clinical use to identify high-risk LC survivors for SPLC.

Methods

Using data from 6325 ever-smokers in the Multiethnic Cohort (MEC) study diagnosed with initial primary lung cancer (IPLC) in 1993-2017, we developed a prediction model for 10-year SPLC risk after IPLC diagnosis using cause-specific Cox regression. We evaluated the model’s clinical utility using decision curve analysis and externally validated it using 2 population-based data—Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO) and National Lung Screening Trial (NLST)—that included 2963 and 2844 IPLC (101 and 93 SPLC cases), respectively.

Results

Over 14 063 person-years, 145 (2.3%) ever-smoking IPLC patients developed SPLC in MEC. Our prediction model demonstrated a high predictive accuracy (Brier score = 2.9, 95% confidence interval [CI] = 2.4 to 3.3) and discrimination (area under the receiver operating characteristics [AUC] = 81.9%, 95% CI = 78.2% to 85.5%) based on bootstrap validation in MEC. Stratification by the estimated risk quartiles showed that the observed SPLC incidence was statistically significantly higher in the 4th vs 1st quartile (9.5% vs 0.2%; P < .001). Decision curve analysis indicated that in a wide range of 10-year risk thresholds from 1% to 20%, the model yielded a larger net-benefit vs hypothetical all-screening or no-screening scenarios. External validation using PLCO and NLST showed an AUC of 78.8% (95% CI = 74.6% to 82.9%) and 72.7% (95% CI = 67.7% to 77.7%), respectively.

Conclusions

We developed and validated a SPLC prediction model based on large population-based cohorts. The proposed prediction model can help identify high-risk LC patients for SPLC and can be incorporated into clinical decision making for SPLC surveillance and screening.

Impact of Low-Dose Computed Tomography Screening for Primary Lung Cancer on Subsequent Risk of Brain Metastasis

INTRODUCTION

Brain metastasis (BM) is one of the most common metastases from primary lung cancer (PLC). Recently, the National Lung Screening Trial revealed the efficacy of low-dose computed tomography (LDCT) screening on LC mortality reduction. Nevertheless, it remains unknown if early detection of PLC through LDCT may be potentially beneficial in reducing the risk of subsequent metastases. Our study aimed to investigate the impact of LDCT screening for PLC on the risk of developing BM after PLC diagnosis.

METHODS

We used the National Lung Screening Trial data to identify 1502 participants who were diagnosed with PLC in 2002 to 2009 and have follow-up data for BM. Cause-specific competing risk regression was applied to evaluate an association between BM risk and the mode of PLC detection-that is, LDCT screen-detected versus non-LDCT screen-detected. Subgroup analyses were conducted in patients with early stage PLC and those who underwent surgery for PLC.

RESULTS

Of 1502 participants, 41.4% had PLC detected through LDCT screening versus 58.6% detected through other methods, for example, chest radiograph or incidental detection. Patients whose PLC was detected with LDCT screening had a significantly lower 3-year incidence of BM (6.5%) versus those without (11.9%), with a cause-specific hazard ratio (HR) of 0.53 (p = 0.001), adjusting for age at PLC diagnosis, PLC stage, PLC histology, and smoking status. This significant reduction in BM risk among PLCs detected through LDCT screening persisted in subgroups of participants with early stage PLC (HR = 0.47, p = 0.002) and those who underwent surgery (HR = 0.37, p = 0.001).

CONCLUSIONS

Early detection of PLC using LDCT screening is associated with lower risk of BM after PLC diagnosis on the basis of a large population-based study.

Association of clinical factors and recent anticancer therapy with COVID-19 severity among patients with cancer: a report from the COVID-19 and Cancer Consortium

BACKGROUND

Patients with cancer may be at high risk of adverse outcomes from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. We analyzed a cohort of patients with cancer and coronavirus 2019 (COVID-19) reported to the COVID-19 and Cancer Consortium (CCC19) to identify prognostic clinical factors, including laboratory measurements and anticancer therapies.

PATIENTS AND METHODS

Patients with active or historical cancer and a laboratory-confirmed SARS-CoV-2 diagnosis recorded between 17 March and 18 November 2020 were included. The primary outcome was COVID-19 severity measured on an ordinal scale (uncomplicated, hospitalized, admitted to intensive care unit, mechanically ventilated, died within 30 days). Multivariable regression models included demographics, cancer status, anticancer therapy and timing, COVID-19-directed therapies, and laboratory measurements (among hospitalized patients).

RESULTS

A total of 4966 patients were included (median age 66 years, 51% female, 50% non-Hispanic white); 2872 (58%) were hospitalized and 695 (14%) died; 61% had cancer that was present, diagnosed, or treated within the year prior to COVID-19 diagnosis. Older age, male sex, obesity, cardiovascular and pulmonary comorbidities, renal disease, diabetes mellitus, non-Hispanic black race, Hispanic ethnicity, worse Eastern Cooperative Oncology Group performance status, recent cytotoxic chemotherapy, and hematologic malignancy were associated with higher COVID-19 severity. Among hospitalized patients, low or high absolute lymphocyte count; high absolute neutrophil count; low platelet count; abnormal creatinine; troponin; lactate dehydrogenase; and C-reactive protein were associated with higher COVID-19 severity. Patients diagnosed early in the COVID-19 pandemic (January-April 2020) had worse outcomes than those diagnosed later. Specific anticancer therapies (e.g. R-CHOP, platinum combined with etoposide, and DNA methyltransferase inhibitors) were associated with high 30-day all-cause mortality.

CONCLUSIONS

Clinical factors (e.g. older age, hematological malignancy, recent chemotherapy) and laboratory measurements were associated with poor outcomes among patients with cancer and COVID-19. Although further studies are needed, caution may be required in utilizing particular anticancer therapies.

CLINICAL TRIAL IDENTIFIER

NCT04354701.

Utilization of COVID-19 Treatments and Clinical Outcomes among Patients with Cancer: A COVID-19 and Cancer Consortium (CCC19) Cohort Study

Among 2,186 U.S. adults with invasive cancer and laboratory-confirmed SARS-CoV-2 infection, we examined the association of COVID-19 treatments with 30-day all-cause mortality and factors associated with treatment. Logistic regression with multiple adjustments (e.g., comorbidities, cancer status, baseline COVID-19 severity) was performed. Hydroxychloroquine with any other drug was associated with increased mortality versus treatment with any COVID-19 treatment other than hydroxychloroquine or untreated controls; this association was not present with hydroxychloroquine alone. Remdesivir had numerically reduced mortality versus untreated controls that did not reach statistical significance. Baseline COVID-19 severity was strongly associated with receipt of any treatment. Black patients were approximately half as likely to receive remdesivir as white patients. Although observational studies can be limited by potential unmeasured confounding, our findings add to the emerging understanding of patterns of care for patients with cancer and COVID-19 and support evaluation of emerging treatments through inclusive prospective controlled trials. SIGNIFICANCE: Evaluating the potential role of COVID-19 treatments in patients with cancer in a large observational study, there was no statistically significant 30-day all-cause mortality benefit with hydroxychloroquine or high-dose corticosteroids alone or in combination; remdesivir showed potential benefit. Treatment receipt reflects clinical decision-making and suggests disparities in medication access.This article is highlighted in the In This Issue feature, p. 1426.

Cost-effectiveness of bivalent versus monovalent vaccines against hand, foot and mouth disease

OBJECTIVES

Enterovirus 71 (EV71) and coxsackievirus A16 (CA16) were responsible for 43.3% (235 123/543 243) and 24.8% (134 607/543 243) of all laboratory-confirmed hand, foot and mouth disease (HFMD) cases during 2010-2015 in China. Three monovalent EV71 vaccines have been licensed in China while bivalent EV71/CA16 vaccines are under development. A comparative cost-effectiveness analysis of bivalent EV71/CA16 versus monovalent EV71 vaccination would be useful for informing the additional value of bivalent HFMD vaccines in China.

METHODS

We used a static model parameterized with the national HFMD surveillance data during 2010-2013, virological HFMD surveillance records from all 31 provinces in mainland China during 2010-2013 and caregiver survey data of costs and health quality of life during 2012-2013. We estimated the threshold vaccine cost (TVC), defined as the maximum additional cost that could be paid for a cost-effective bivalent EV71/CA16 vaccine over a monovalent EV71 vaccine, as the outcome. The base case analysis was performed from a societal perspective. Several sensitivity analyses were conducted by varying assumptions governing HFMD risk, costs, discounting and vaccine efficacy.

RESULTS

In the base case, choosing the bivalent EV71/CA16 over monovalent EV71 vaccination would be cost-effective only if the additional cost of the bivalent EV71/CA16 compared with the monovalent EV71 vaccine is less than €4.7 (95% CI 4.2-5.2). Compared with the TVC in the base case, TVC increased by up to €8.9 if all the test-negative cases were CA16-HFMD; decreased by €1.1 with an annual discount rate of 6% and exclusion of the productivity loss; and increased by €0.14 and €0.3 with every 1% increase in bivalent vaccine efficacy against CA16-HFMD and differential vaccine efficacy against EV71-HFMD, respectively.

CONCLUSIONS

Bivalent EV71/CA16 vaccines can be cost-effective compared with monovalent EV71 vaccines, if suitably priced. Our study provides further evidence for determining the optimal use of HFMD vaccines in routine paediatric vaccination programme in China.

[Application of stretched exponential diffusion-weighted imaging model in quantitative diagnosis of nonalcoholic fatty liver disease: in a rabbit model]

Objective: To evaluate the feasibility of diffusion parameters obtained from mono-exponential and stretched exponential diffusion-weighted imaging models in staging of nonalcoholic fatty liver disease and compare the diagnosis ability of nonalcoholic steatohepatitis. Methods: Thirty-two 12 -week-old male New Zealand rabbits, about 2.5 kg of each, were randomly divided into five groups. To obtained different severity groups of NAFLD, a variety of diet (from standard to high-fat, high cholesterol chow) were feed for different periods before liver diffusion imaging was performed by using 3.0 T MR imaging system (Discovery 750W GE health care), the value of ADC, stretched exponential model parameters distributed diffusion coefficient (DDC) and α (water molecular diffusion heterogeneity index) were measured. Liver specimens were obtained for pathological grading (NAFLD activity scoring system). The diffusion parameters of each group of NAFLD were compared by ANOVA, LSD-t test was utilized to pairwise comparison between different grades of NAFLD. Spearman rank correlation analysis was used to evaluate the correlation between ADC, DDC, α and different severity groups of NAFLD. ROC curve was compared to evaluate the diagnostic efficiency of MR parameters for NASH. Results: α was significant different between borderline and NASH groups (0.65±0.05 vs 0.72±0.07; P<0.05); ADC and DDC showed no statistical difference between borderline and NASH groups (ADC:(1.09±0.14)×10(-3) vs (1.04±0.24)×10(-3) mm(2)/s; DDC: (0.73±0.08)×10(-3) vs (0.66±0.19)×10(-3) mm(2)/s; P>0.05); ADC and DDC were negatively correlated with NAFLD, and the correlation coefficients were -0.552, -0.596, respectively (P<0.05). α was found to be positively correlated with advancement of NAFLD, the correlation coefficient was 0.729 (P<0.05).In terms of the diagnostic efficiency of NASH, the AUC of ADC, DDC and α were 0.736, 0.784, 0.900, respectively, α was significantly greater than ADC in diagnosis of NASH (P<0.05). Conclusion: Stretched exponential model parameter α (water molecular diffusion heterogeneity index) could be utilized to identify NAFLD. α may provide more information and improve the staging of NASH compared with conventional diffusion parameters.

Effects of Δ(9)-tetrahydrocannabinol (THC) on human amniotic epithelial cell proliferation and migration

BACKGROUND

The deleterious effects of cannabis consumption for fertility and pregnancy outcome are recognized for years. The main psychoactive molecule of cannabis, Δ(9)-tetrahydrocannabinol (THC) is able to cross the placenta barrier and cause alterations in fetal growth, low birth weight and preterm labor. However, the effects of THC on the human placenta amnion are still unknown.

METHODS

The distributions of CB1R and CB2R in human amnion tissues were observed by immunohistochemistry (IHC). Human amniotic epithelial cell proliferation and migration in response to THC treatment were measured by MTS and transwell assays, respectively. The PCR array was performed to study the key regulators involved in the cell migration. The protein levels of CB1R, CB2R in amnion tissues and MMP2, MMP9 in cells were detected by western blotting. Small interfering RNAs (siRNAs) were used to knockdown MMP2 and MMP9 in WISH cells.

RESULTS

Our results indicated that both CB1R and CB2R primarily identified in the epithelial layer of human placental amnion tissue. The CB1R expression in the amnion tissue was higher in the preterm group than normal control. High-dose of THC (30uM, but not 20 and 10uM) significantly inhibited (p<0.01) human amniotic epithelial cell lines (WISH) proliferation. Meanwhile, THC at both 10uM and 20uM (p<0.05) significantly suppressed cells migration in both WISH and primary human amniotic epithelial cells. The PCR array data and siRNA experiments demonstrated that MMP2/9 were tightly involved in the regulation of THC-inhibited cell migration in WISH cells.

CONCLUSION

These results suggested that THC inhibited the migration of human amniotic epithelial cell through the regulation of MMP2 and MMP9, which in turn altered the development of the amnion during the gestation and partially resulted in preterm labor and other adverse pregnancy outcomes.

[Application of swallow tail appearance in patients with Parkinson's disease]

OBJECTIVE

To evaluate the clinical value of swallow tail appearance in detecting the patient with Parkinson's disease at 3.0 T MRI.

METHODS

A total of 42 patients with clinical diagnosis of Parkinson's disease(PD) and 27 age-matched normal controls underwent the brain MR examination with conventional and E-SWAN sequences. Patients were divided into 4 groups based on Hoehn-Yahr stage and 2 groups according the treatment condition (treated, untreated). Substantia nigra (SN) was selected as region of interest (ROI) and observed the swallow tail appearance on magnitude imagines of E-SWAN sequence. Nonparametric test was used for comparison between patients groups and normal controls. There was statistically difference if the P value was lower than 0.05.

RESULTS

The swallow tail appearance lost was significantly correlated with Parkinson's disease (P=0.000). The swallow tail appearance lost was not correlated with the usage of drugs(P=0.833) and Hoehn-Yahr stage(P=0.189). The sensitivity of diagnosis of PD by using the swallow tail disappearance was 95.5% (42/44), the specificity was 83.3% (25/30), the accuracy was 90.5%(67/74).

CONCLUSIONS

Assessing the substantia nigra on E-SWAN for the typical swallow tail appearance has potential to become a new and easy applicable 3.0 T MRI diagnostic tool for PD, however, it was meaningless for prognosis and staging.

Mineralization of sulfamethizole in photo-Fenton and photo-Fenton-like systems

In this investigation, UV/H2O2, UV/H2O2/Fe(2+) (photo-Fenton) and UV/H2O2/Fe(3+) (photo-Fenton-like) systems were used to mineralize sulfamethizole (SFZ). The optimal doses of H2O2 (1-20 mM) in UV/H2O2 and iron (0.1-1 mM) in photo-Fenton and photo-Fenton-like systems were determined. Direct photolysis by UV irradiation and direct oxidation by added H2O2, Fe(2+) and Fe(3+) did not mineralize SFZ. The optimal dose of H2O2 was 10 mM in UV/H2O2 and that of iron (Fe(2+) or Fe(3+)) was 0.2 mM in both UV/H2O2/Fe(2+) and UV/H2O2/Fe(3+) systems. Under the best experimental conditions and after 60 min of reaction, the SFZ mineralization percentages in UV/H2O2, UV/H2O2/Fe(2+) and UV/H2O2/Fe(3+) systems were 16, 90 and 88%, respectively. The UV/H2O2/Fe(2+) and UV/H2O2/Fe(3+) systems effectively mineralized SFZ.

Effect of atorvastatin on plasma NT-proBNP and inflammatory cytokine expression in patients with heart failure

The aim of this study was to explore the effect of atorvastatin intervention on plasma N-terminal pro-B-type natriuretic peptide (NT-proBNP) and inflammatory cytokine levels in patients with heart failure (HF). One hundred and twenty-three HF patients were selected from our hospital and randomly divided into control (N = 61) and observation (N = 62) groups; the former received conventional treatment, while the latter were given conventional treatment combined with atorvastatin. Plasma NT-proBNP, inflammatory cytokines [high-sensitive C-reactive protein (hs-CRP), interleukin (IL)-6, IL-10] and cardiac function [left ventricular end-diastolic dimension (LVEDD), left ventricular ejection fraction (LVEF), end-diastolic maximum flow rate ratio (E/A)] were compared among groups. The effective rate of treating HF significantly increased after atorvastatin treatment. The plasma NT-proBNP, IL-6, IL-10, hs-CRP, and LVEDD levels significantly decreased (P < 0.05), while the LVEF and E/A levels significantly increased (P < 0.05) in the observation group compared to the control group and before intervention. The NT-proBNP and cytokine levels significantly differed among patients with different classes of heart function (P < 0.05); the NT-proBNP and cytokine levels increased with the severity of heart function. Pearson's correlation analysis revealed a negative correlation between the NT-proBNP and inflammatory cytokine levels and LVEF and E/A values, and a positive correlation between these factors and LVEDD (P < 0.05). In conclusion, atorvastatin significantly improves cardiac function; the mechanism atorvastatin action was related to the decrease in plasma NT-proBNP and inflammatory cytokine levels.

Preliminary epidemiological assessment of MERS-CoV outbreak in South Korea, May to June 2015

South Korea is experiencing the largest outbreak of Middle East respiratory syndrome coronavirus infections outside the Arabian Peninsula, with 166 laboratory-confirmed cases, including 24 deaths up to 19 June 2015. We estimated that the mean incubation period was 6.7 days and the mean serial interval 12.6 days. We found it unlikely that infectiousness precedes symptom onset. Based on currently available data, we predict an overall case fatality risk of 21% (95% credible interval: 14–31).