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PurposeThe new 8th American Joint Committee on Cancer (AJCC)/International Union for Cancer Control (UICC) lung cancer staging system was developed and internally validated using the International Association for the Study of Lung Cancer (IASLC) database, but external validation is needed. The goal of this study is to validate the discriminatory ability and prognostic performance of this new staging system in a larger, independent non-small cell lung cancer (NSCLC) cohort with greater emphasis on North American patients.MethodsA total of 858,909 NSCLC cases with one malignant primary tumor collected from 2004 to 2013 in the National Cancer Database (NCDB) were analyzed. The primary coding guidelines of the Collaborative Staging Manual and Coding Instructions for the new 8th edition AJCC/UICC lung cancer staging system was used to define the new T, M and TNM stages for all patients in the database. Kaplan-Meier curves, Cox regression models and time-dependent receiver operating characteristics were used to compare the discriminatory ability and prognostic performance of the 7th and the revised 8th T, M categories and overall stages.ResultsWe demonstrated that the 8th staging system provides better discriminatory ability than the 7th staging system and predicts prognosis for NSCLC patients using the NCDB. There were significant survival differences between adjacent groups defined by both clinical staging and pathologic staging systems. These staging parameters were significantly associated with survival after adjusting for other factors.ConclusionsThe updated T, M, and overall TNM stage of the 8th staging system show improvement compared to the 7th edition in discriminatory ability between adjacent subgroups and are independent predictors for prognosis.

Background With the expansion of non–small cell lung cancer (NSCLC) screening methods, the percentage of cases with early‐stage NSCLC is anticipated to increase. Yet it remains unclear how the type and case volume of the health care facility at which treatment occurs may affect surgery selection and overall survival for cases with early‐stage NSCLC. Methods A total of 332,175 cases with the American Joint Committee on Cancer (AJCC) TNM stage I and stage II NSCLC who were reported to the National Cancer Data Base (NCDB) by 1302 facilities were studied. Facility type was characterized in the NCDB as community cancer program (CCP), comprehensive community cancer program (CCCP), academic/research program (ARP), or integrated network cancer program (INCP). Each facility type was dichotomized further into high‐volume or low‐volume groups based on the case volume. Multivariate Cox proportional hazard models, the logistic regression model, and propensity score matching were used to evaluate differences in survival and surgery selection among facilities according to type and volume. Results Cases from ARPs were found to have the longest survival (median, 16.4 months) and highest surgery rate (74.8%), whereas those from CCPs had the shortest survival (median, 9.7 months) and the lowest surgery rate (60.8%). The difference persisted when adjusted by potential confounders. For cases treated at CCPs, CCCPs, and ARPs, high‐volume facilities had better survival outcomes than low‐volume facilities. In facilities with better survival outcomes, surgery was performed for a greater percentage of cases compared with facilities with worse outcomes. Conclusions For cases with early‐stage NSCLC, both facility type and case volume influence surgery selection and clinical outcome. Higher surgery rates are observed in facilities with better survival outcomes.

Immune-related adverse events (irAE) may affect almost any organ system and occur at any point during treatment with immune checkpoint inhibitors (ICI). We present a patient with advanced lung cancer receiving antiprogrammed death 1 checkpoint inhibitor who developed a delayed-onset visual irAE treated with corticosteroids. Through assessment of longitudinal biospecimens, we analyzed serial autoantibodies, cytokines, and cellular populations. Months after ICI initiation and preceding clinical toxicity, the patient developed broad increases in cytokines (most notably interleukin-6 (IL-6), interferon-γ (IFNγ), C-X-C motif chemokine ligand 2 (CXCL2), and C–C motif chemokine ligand 17 (CCL17)), autoantibodies (including anti-angiotensin receptor, α-actin, and amyloid), CD8 T cells, and plasmablasts. Such changes were not observed in healthy controls and ICI-treated patients without irAE. Administration of corticosteroids resulted in immediate and profound decreases in cytokines, autoantibodies, and inflammatory cells. This case highlights the potential for late-onset changes in humoral and cellular immunity in patients receiving ICI. It also demonstrates the biologic effects of corticosteroids on these parameters. Application of humoral and cellular immune biomarkers across ICI populations may inform toxicity monitoring and management.

Importance: Nomogram prognostic models can facilitate cancer patient treatment plans and patient enrollment in clinical trials. Objective: The primary objective is to provide an updated and accurate prognostic model for predicting the survival of advanced non-small-cell lung cancer (NSCLC) patients, and the secondary objective is to validate a published nomogram prognostic model for NSCLC using an independent patient cohort. Design: 1817 patients with advanced NSCLC from the control arms of 4 Phase III randomized clinical trials were included in this study. Data from 524 NSCLC patients from one of these trials were used to validate a previously published nomogram and then used to develop an updated nomogram. Patients from the other 3 trials were used as independent validation cohorts of the new nomogram. The prognostic performances were comprehensively evaluated using hazard ratios, integrated area under the curve (AUC), concordance index, and calibration plots. Setting: General community. Main outcome: A nomogram model was developed to predict overall survival in NSCLC patients. Results: We demonstrated the prognostic power of the previously published model in an independent cohort. The updated prognostic model contains the following variables: sex, histology, performance status, liver metastasis, hemoglobin level, white blood cell counts, peritoneal metastasis, skin metastasis, and lymphocyte percentage. This model was validated using various evaluation criteria on the 3 independent cohorts with heterogeneous NSCLC populations. In the SUN1087 patient cohort, the continuous risk score output by the nomogram achieved an integrated area under the receiver operating characteristics (ROC) curve of 0.83, a log-rank P -value of 3.87e−11, and a concordance index of 0.717. In the SAVEONCO patient cohort, the integrated area under the ROC curve was 0.755, the log-rank P -value was 4.94e−6 and the concordance index was 0.678. In the VITAL patient cohort, the integrated area under the ROC curve was 0.723, the log-rank P -value was 1.36e−11, and the concordance index was 0.654. We implemented the proposed nomogram and several previously published prognostic models on an online Web server for easy user access. Conclusions: This nomogram model based on basic clinical features and routine lab testing predicts individual survival probabilities for advanced NSCLC and exhibits cross-study robustness.

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Abstract. As a distributed computing platform, Hadoop provides an effective way to handle big data. In Hadoop, the completion time of job will be delayed by a straggler. Although the definitive cause of the straggler is hard to detect, speculative execution is usually used for dealing with this problem, by simply backing up those stragglers on alternative nodes. In this paper, we design a new Speculative Execution algorithm based on C4.5 Decision Tree, SECDT, for Hadoop. In SECDT, we speculate completion time of stragglers and also of backup tasks, based on a kind of decision tree method: C4.5 decision tree. After we speculate the completion time, we compare the completion time of stragglers and of the backup tasks, calculating their differential value, and selecting the straggler with the maximum differential value to start the backup task. Experiment result shows that the SECDT can predict execution time more accurately than other speculative execution methods, hence reduce the job completion time.

In Dynamic Symmetric Searchable Encryption (DSSE), forward privacy ensures that previous search queries cannot be associated with future updates, while backward privacy guarantees that subsequent search queries cannot be associated with deleted documents in the past. In this work, we propose a generic forward and backward-private DSSE scheme, which is, to the best of our knowledge, the first practical and non-interactive Type-II backward-private DSSE scheme not relying on trusted execution environments. To this end, we first introduce a new cryptographic primitive, named Symmetric Revocable Encryption (SRE), and propose a modular construction from some succinct cryptographic primitives. Then we present our DSSE scheme based on the proposed SRE, and instantiate it with lightweight symmetric primitives. At last, we implement our scheme and compare it with the most efficient Type-II backward-private scheme to date (Demertzis et al., NDSS 2020). In a typical network environment, our result shows that the search in our scheme outperforms it by 2 − 11× under the same security notion.