A clinical nomogram and heat map for assessing survival in patients with stage I non-small cell lung cancer after complete resection

Cao, Xun; Zheng, Yuzhen; Liao, Hongying; Guo, Xiang; Li, Yong; Wang, Zhen; Zhang, Li; Wang, Xudong; Wang, Xin

doi:10.1177/1758835920970063

Cited by 17 publications

(20 citation statements)

References 29 publications

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“…For patients treated with ICIs plus chemotherapy, our study also demonstrated that bone metastasis was linked to a shortened PFS. The C-index, AUC, and calibration curves implied the predictive accuracy of the current model as reported models, but the AUC of the nomogram to predict PFS at 3 months was relatively low in the validation cohort, which means that the model had a weak ability to predict PFS at 3 months but was better able to predict PFS at 6 and 12 months (14,41). We attribute this to several causes.…”

Section: Discussionmentioning

confidence: 80%

Development and Validation of a Nomogram for Predicting Prognosis to Immune Checkpoint Inhibitors Plus Chemotherapy in Patients With Non-Small Cell Lung Cancer

et al. 2021

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BackgroundImmune checkpoint inhibitors (ICIs) plus chemotherapy improved the prognosis of patients with non-small cell lung cancer (NSCLC); however, reliable prognostic biomarkers are lacking. We explored factors associated with prognosis and developed a predictive model.MethodsWe retrospectively analyzed 130 consecutive stage IIIA–IVB NSCLC patients treated with ICIs combined with chemotherapy. Cox univariate and multivariate proportional hazards regression analyses were used to identify prognostic factors associated with progression-free survival (PFS). A nomogram was developed based on key factors in the training cohort (n = 86) and evaluated in the validation cohort (n = 44). According to the nomogram-based total point scores, we divided patients into low- and high-risk groups.ResultsIn the training cohort, bone metastases (p = 0.017) and an increased derived neutrophil-to-lymphocyte ratio (p = 0.018) were significantly associated with poor PFS, while smoking (p = 0.007) and programmed death-ligand 1 (PD-L1) ≥50% (p = 0.001) were associated with improved PFS. A nomogram based on these factors was developed to predict PFS at 3, 6, and 12 months. The C-index of the nomogram to predict PFS was 0.725 (95% CI: 0.711–0.739) in the training cohort and 0.688 (95% CI: 0.665–0.711) in the validation cohort. The area under the curve (AUC) exhibited an acceptable discriminative ability, and calibration curves demonstrated a consistency between the actual results and predictions. In the training cohort, the median PFS (mPFS) was 12.3 and 5.7 months in the low- and high-risk groups, respectively (p < 0.001). In the validation cohort, the mPFS was 12.6 and 6.2 months in the low- and high-risk groups, respectively (p = 0.021).ConclusionsA predictive nomogram was developed to help clinicians assess prognosis early for advanced NSCLC patients who received ICI plus chemotherapy.

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Section: Discussionmentioning

confidence: 80%

Development and Validation of a Nomogram for Predicting Prognosis to Immune Checkpoint Inhibitors Plus Chemotherapy in Patients With Non-Small Cell Lung Cancer

et al. 2021

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“…Furthermore, validation of the model we established was accomplished by bootstrap resampling. Although previous studies have successfully reported nomograms to predict the postoperative survival and recurrence in stage IA NSCLC, they didn't include inflammatory biomarkers (7,(56)(57)(58)(59). To our knowledge, this study is the first large cohort study to create a nomogram combining inflammatory biomarkers and other clinicopathological factors to predict CSS and DFS probability in stage I adenocarcinoma patients.…”

Section: Discussionmentioning

confidence: 98%

Prognostic Value of Inflammatory Biomarkers in Patients With Stage I Lung Adenocarcinoma Treated With Surgical Dissection

et al. 2021

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ObjectiveInflammation plays a crucial role in tumorigenesis and progression. Our purpose was to investigate the prognostic value of neutrophil-to-lymphocyte ratio (NLR), systemic inflammation response index (SIRI) and systemic immune-inflammation index (SII), and develop a nomogram to predict the cancer-specific survival (CSS) and disease-free survival (DFS) of stage I lung adenocarcinoma patients.Methods1431 patients undergoing surgical resection with pathologically confirmed stage I lung adenocarcinoma were reviewed. The optimal cut-off values for NLR, SII, and SIRI were defined by the receiver operating characteristic (ROC) curve. Cox proportional hazards regression analyses were performed to recognize factors significantly correlated with CSS and DFS to construct the nomogram. The value of adjuvant chemotherapy on model-defined high-risk and low-risk patients was further explored.ResultsThe cohort had a median follow-up time of 63 months. Multivariate analysis revealed that higher NLR (≥2.606), higher SIRI (≥0.705), higher SII (≥580.671), later T stage, histological pattern with solid or micropapillary components and radiologic features with solid nodules were significantly associated with worse CSS and DFS. The concordance index (C-index) of the nomogram established by all these factors was higher than that of the TNM staging system both in CSS (validation set 0.778 vs 0.652) and DFS (validation set 0.758 vs 0.695). Furthermore, the value of the established nomogram on risk stratification in stage I lung adenocarcinoma patients was validated.ConclusionsHigher NLR, SII and SIRI pretreatment were associated with worse survival outcomes. A practical nomogram based on these three inflammatory biomarkers may help clinicians to precisely stratify stage I lung adenocarcinoma patients into high- and low-risk and implement individualized treatment.

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“…For resected NSCLC (stage I-IIIa) [19], a clinical nomogram built on sex, age, histology, sampled lymph nodes, T and N stage achieved higher C-index than that of the seventh edition American Joint Committee on Cancer TNM staging system for predicting OS (primary cohort, 0.71 v 0.68, respectively; P .01; validation cohort, 0.67 v 0.64, respectively; P .06). Another study devised an effective clinical nomogram for assessing the survival of patients with stage I NSCLC receiving complete resection [25]. The nomogram built on age, sex, tumor size, and visceral pleural invasion had C-indices of 0.694 (95% CI 0.651-0.737) for predicting OS and 0.653 (95% CI 0.61-0.696) for DFS.…”

Section: Discussionmentioning

confidence: 99%

Prognostic Nomogram to Predict the Overall Survival of Patients with “driver-gene-negative” Lung Adenocarcinoma (LUAD) and Its’ Biological Basis Deciphering

Zhu

Yang

Shan

et al. 2021

Preprint

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Objectives: Assessing the prognosis of patients with “driver-gene-negative” lung adenocarcinoma (LUAD patients negative for EGFR, KRAS, BRAF, HER2, MET, ALK, RET and ROS1 were identified as “driver-gene-negative”) is of significant clinical importance. We aimed to devise a prognostic nomogram for this LUAD subgroup and to define its biological basis.Materials and methods: Prognostic nomogram were established based on a retrospective study of 294 patients with surgical resected “driver-gene-negative” LUAD at The First Affiliated Hospital of Sun Yat-sen University between September 2003 and June 2015. The concordance index (C-index) and calibration curve were used to determine its predictive accuracy and discriminatory capacity. Patients were classified into low- and high-risk subgroups according to nomogram scores. To define the biological basis, we carried out gene set enrichment analysis in an independent dataset of 49 “driver-gene-negative” LUAD patients.Results: The nomogram built on the independent factors including CTC, age and stage achieved C-index of 0.785 [95% confidence interval (CI) 0.753-0.817] for predicting OS of “driver-gene-negative” LUAD. The calibration curves for OS probabilities showed a good agreement between the nomogram prediction and actual observation. High-risk patients had shorter OS [hazard ratio (HR) = 7.43, 95% CI 5.20-10.42, p<0.0001]. The genetic analysis suggested the biological basis for the role of the predictive model may be due to changes in cell proliferation, metabolism and neurological disease, indicating a relationship between increased proliferative potential and preferential poor prognosis.Conclusions: The prognostic nomogram showed promising prediction efficacy and is expected to predict the prognosis of “driver-gene-negative” LUAD. The easy-to-use nomogram and the enriched pathways can help clinical decision-making, guide follow-up planning, and develop new therapeutic targets.

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A clinical nomogram and heat map for assessing survival in patients with stage I non-small cell lung cancer after complete resection

Cited by 17 publications

References 29 publications

Development and Validation of a Nomogram for Predicting Prognosis to Immune Checkpoint Inhibitors Plus Chemotherapy in Patients With Non-Small Cell Lung Cancer

Development and Validation of a Nomogram for Predicting Prognosis to Immune Checkpoint Inhibitors Plus Chemotherapy in Patients With Non-Small Cell Lung Cancer

Prognostic Value of Inflammatory Biomarkers in Patients With Stage I Lung Adenocarcinoma Treated With Surgical Dissection

Prognostic Nomogram to Predict the Overall Survival of Patients with “driver-gene-negative” Lung Adenocarcinoma (LUAD) and Its’ Biological Basis Deciphering

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