Survival Analysis and Prediction Model for Pulmonary Sarcomatoid Carcinoma Based on SEER Database

Survival analysis and nomogram for pulmonary sarcomatoid carcinoma: an SEER analysis and external validation

OBJECTIVE

Uncommon and particularly deadly, pulmonary sarcomatoid carcinoma (PSC) is an aggressive type of lung cancer. This research aimed to create a risk categorisation and nomogram to forecast the overall survival (OS) of patients with PSC.

METHODS

To develop the model, 899 patients with PSC were taken from the Surveillance, Epidemiology, and End Results database from the USA. We also used an exterior verification sample of 34 individuals with PSC from Fujian Provincial Hospital in China. The Cox regression hazards model and stepwise regression analysis were done to screen factors in developing a nomogram. The nomogram's ability to discriminate was measured employing the area under a time-dependent receiver operating characteristic curve (AUC), the concordance index (C-index) and the calibration curve. Decision curve analysis (DCA) and integrated discrimination improvement (IDI) were used to evaluate the nomogram to the tumour-node-metastasis categorisation developed by the American Joint Committee on Cancer (AJCC-TNM), eighth edition, and an additional sample confirmed the nomogram's accuracy. We further developed a risk assessment system based on nomogram scores.

RESULTS

Six independent variables, age, sex, primary tumour site, pathological group, tumour-node-metastasis (TNM) clinical stage and therapeutic technique, were chosen to form the nomogram's basis. The nomogram indicated good discriminative ability with the C-index (0.763 in the training cohort and 0.746 in the external validation cohort) and time-dependent AUC. Calibration plots demonstrated high congruence between the prediction model and real-world evidence in both the validation and training cohorts. Nomogram outperformed the AJCC-TNM eighth edition classification in both DCA and IDI. Patients were classified into subgroups according to their risk ratings, and significant differences in OS were observed between them (p<0.001).

CONCLUSION

We conducted a survival analysis and nomogram for PSC. This developed nomogram holds potential to serve as an efficient tool for clinicians in prognostic modelling.

Clinical outcomes of radical radiotherapy for pulmonary sarcomatoid carcinoma

PURPOSE

Pulmonary sarcomatoid carcinoma (PSC) is recognized for its aggressiveness and poor prognosis. The role of radical radiotherapy in PSC remains uncertain due to its scarcity and limited data. In the absence of an effective systemic agent, this study aims to explore the possibility of cure and to investigate potential prognostic factors and treatment outcomes.

MATERIALS AND METHODS

From January 2005 to December 2021, 149 PSC patients were identified. Among 62 patients who received radiotherapy for lung lesions, 25 who underwent palliative radiotherapy and 16 who underwent surgery were excluded.

RESULTS

The median patient age was 71 years. The majority were male, and 17 patients (81.0%) were diagnosed at an advanced stage. After radical radiotherapy, distant metastasis (47.6%) was the most common site of failure, while the local recurrence rate was quite low (9.5%). Eventually, five patients (26.3%) demonstrated either a partial response or complete remission, including three complete remissions with durable responses. The median progression-free survival (PFS) and overall survival were 4.6 months and 7.9 months, respectively. Univariate and multivariate analyses revealed that a tumor size >5 cm was associated with a worse prognosis (p = 0.045), while a radiation dose >58 GyEQD2 was significantly associated with better PFS (p = 0.038).

CONCLUSION

This study demonstrates clinical outcomes after radical radiotherapy in managing PSC, suggesting tumor size and radiation dose could be a predictor of a systemic response. Given the known bad prognosis but complete remission could be achieved in certain subgroups, future research should explore the potential strategies using radical radiotherapy for this challenging patient population.

An advanced pulmonary sarcomatoid carcinoma patient harboring a BRAFV600E mutation responds to dabrafenib and trametinib: a case report and literature review

Background

The pulmonary sarcomatoid carcinoma (PSC) is a rare and aggressive subtype of NSCLC with rapid progression and poor prognosis, and is resistant to conventional chemotherapy. Most PSC cases have potential targetable genomic alterations. Approximately 7% of PSC patients have BRAF mutations, and the efficacy of dabrafenib and trametinib in BRAFV600E mutated PSC is unclear.

Case presentation

Our report describes a patient with mutated BRAFV600E PSC who underwent surgery and adjuvant chemotherapy early but quickly relapsed. Both chemotherapy and immunotherapy were ineffective for him, combined dabrafenib and trametinib produced a 6-month progression-free survival, and a partial response was observed in the tumor response evaluation. As a result of financial pressure, he stopped taking the targeted drugs, and his disease rapidly progressed.

Conclusion

Dabrafenib combined with trametinib provides partial remission in patients with advanced PSC with BRAFV600E mutations, and large-scale NGS panels could offer more options for PSC treatment.

Individual risk and prognostic value prediction by machine learning for distant metastasis in pulmonary sarcomatoid carcinoma: a large cohort study based on the SEER database and the Chinese population

Background

This study aimed to develop diagnostic and prognostic models for patients with pulmonary sarcomatoid carcinoma (PSC) and distant metastasis (DM).

Methods

Patients from the Surveillance, Epidemiology, and End Results (SEER) database were divided into a training set and internal test set at a ratio of 7 to 3, while those from the Chinese hospital were assigned to the external test set, to develop the diagnostic model for DM. Univariate logistic regression was employed in the training set to screen for DM-related risk factors, which were included into six machine learning (ML) models. Furthermore, patients from the SEER database were randomly divided into a training set and validation set at a ratio of 7 to 3 to develop the prognostic model which predicts survival of patients PSC with DM. Univariate and multivariate Cox regression analyses have also been performed in the training set to identify independent factors, and a prognostic nomogram for cancer-specific survival (CSS) for PSC patients with DM.

Results

For the diagnostic model for DM, 589 patients with PSC in the training set, 255 patients in the internal and 94 patients in the external test set were eventually enrolled. The extreme gradient boosting (XGB) algorithm performed best on the external test set with an area under the curve (AUC) of 0.821. For the prognostic model, 270 PSC patients with DM in the training and 117 patients in the test set were enrolled. The nomogram displayed precise accuracy with AUC of 0.803 for 3-month CSS and 0.869 for 6-month CSS in the test set.

Conclusion

The ML model accurately identified individuals at high risk for DM who needed more careful follow-up, including appropriate preventative therapeutic strategies. The prognostic nomogram accurately predicted CSS in PSC patients with DM.

Integrated Clinical, Molecular and Immunological Characterization of Pulmonary Sarcomatoid Carcinomas Reveals an Immune Escape Mechanism That May Influence Therapeutic Strategies

Pulmonary sarcomatoid carcinoma (PSC) has highly aggressive biological behaviour and poor clinical outcomes, raising expectations for new therapeutic strategies. We characterized 179 PSC by immunohistochemistry, next-generation sequencing and in silico analysis using a deep learning algorithm with respect to clinical, immunological and molecular features. PSC was more common in men, older ages and smokers. Surgery was an independent factor (p < 0.01) of overall survival (OS). PD-L1 expression was detected in 82.1% of all patients. PSC patients displaying altered epitopes due to processing mutations showed another PD-L1-independent immune escape mechanism, which also significantly influenced OS (p < 0.02). The effect was also maintained when only advanced tumour stages were considered (p < 0.01). These patients also showed improved survival with a significant correlation for immunotherapy (p < 0.05) when few or no processing mutations were detected, although this should be interpreted with caution due to the small number of patients studied. Genomic alterations for which there are already approved drugs were present in 35.4% of patients. Met exon 14 skipping was found more frequently (13.7%) and EGFR mutations less frequently (1.7%) than in other NSCLC. In summary, in addition to the divergent genomic landscape of PSC, the specific immunological features of this prognostically poor subtype should be considered in therapy stratification.

Demographics and Clinicopathologic Profile of Pulmonary Sarcomatoid Carcinoma with Survival Analysis and Genomic Landscape

Background: Pulmonary sarcomatoid carcinoma (PSC) is a rare subtype of non-small cell lung cancer (NSCLC) with an aggressive clinical nature and poor prognosis. With novel targeted therapeutics being developed, new ways to effectively treat PSC are emerging. In this study, we analyze demographics, tumor characteristics, treatment modalities, and outcomes of PSC and genetic mutations in PSC. Methods: Data from the Surveillance, Epidemiology, and End Results (SEER) database were reviewed to analyze cases of pulmonary sarcomatoid carcinoma from 2000 to 2018. The molecular data with the most common mutations in PSC were extracted from the Catalogue Of Somatic Mutations in Cancer (COSMIC) database. Results: A total of 5259 patients with PSC were identified. Most patients were between 70 and 79 years of age (32.2%), male (59.1%), and Caucasian (83.7%). The male-to-female ratio was 1.45:1. Most tumors were between 1 and 7 cm in size (69.4%) and poorly differentiated (grade III) (72.9%). The overall 5-year survival was 15.6% (95% confidence interval (95% CI) = 14.4-16.9)), and the cause-specific 5-year survival was 19.7% (95% CI = 18.3-21.1). The five-year survival for those treated with each modality were as follows: chemotherapy, 19.9% (95% CI = 17.7-22.2); surgery, 41.7% (95% CI = 38.9-44.6); radiation, 19.1% (95% CI = 15.1-23.5); and multimodality therapy (surgery and chemoradiation), 24.8% (95% CI = 17.6-32.7). On multivariable analysis, age, male gender, distant stage, tumor size, bone metastasis, brain metastasis, and liver metastasis were associated with increased mortality, and chemotherapy and surgery were associated with reduced mortality (p < 0.001). The best survival outcomes were achieved with surgery. The most common mutations identified in COSMIC data were TP53 31%, ARID1A 23%, NF1 17%, SMARCA4 16%, and KMT2D 9%. Conclusions: PSC is a rare and aggressive subtype of NSCLC, usually affecting Caucasian males between 70 and 79. Male gender, older age, and distant spread were associated with poor clinical outcomes. Treatment with surgery was associated with better survival outcomes.

Gastrointestinal bleeding due to jejunal metastasis of pleomorphic lung carcinoma: a case report

Gastrointestinal metastasis of pleomorphic lung cancer presents with nonspecific manifestations, leading to delayed diagnosis. Herein, the authors report the case of a 56-year-old patient who presented with gastrointestinal bleeding due to pleomorphic lung carcinoma.

Case presentation

A 56-year-old patient presented to the emergency department with melena. On examination, he was hemodynamically stable. He had a sensitive and mobile mass in the periumbilical region. A thoracoabdominal computed tomography scan showed a mass of the right apical superior lobe measuring 4 cm and a lobulated jejunal mass measuring 10 cm. A percutaneous biopsy of the lung tumor revealed primary pleomorphic lung carcinoma. The authors performed a midline laparotomy and made a bowel resection with an end-to-end anastomosis. The postoperative course was marked by severe nosocomial pneumonia, leading to septic shock and death. The histopathologic examination concluded with a metastatic lesion of pleomorphic lung carcinoma.

Clinical discussion

The authors reported a rare case of jejunal metastasis of pleomorphic lung cancer. Pleomorphic carcinoma of the lung is a rare pathology that accounts for 0.1-0.4% of nonsmall-cell lung cancer. The prognosis is poor. In the presence of gastrointestinal bleeding caused by small bowel metastases of pleomorphic lung cancer, surgery is the treatment of choice.

Conclusions

Small bowel metastasis of pleomorphic lung cancer is rare. Surgical treatment is the treatment of choice. The authors highlight the importance of suspecting gastrointestinal metastases in patients with pleomorphic lung cancer in the presence of nonspecific digestive symptoms.

Survival outcomes and prognostic factors of lung cancer patients with the MET exon 14 skipping mutation: A single-center real-world study

Introduction

The MET exon 14 skipping (METex14) mutation is an important oncogenic driver in lung cancer. We performed a retrospective analysis of clinical data from lung cancer patients with the METex14 mutation to analyze their survival outcomes and associated prognostic factors.

Methods

A one-step reverse transcription-polymerase chain reaction to examine the presence of the METex14 mutation was performed using RNA samples from 1374 lung cancer patients with no detected EGFR and ALK mutations. Pathological features and immunohistochemistry (IHC) results for c-MET were analyzed in patients with METex14-positive tumors.

Results

METex14 was identified in 69 patients with lung cancer, including 53 adenocarcinoma (ADC) and 16 non-ADC patients. In comparison with patients without the METex14 mutation, lung cancer patients harboring the METex14 mutation were generally elderly individuals, never-smokers, and had poor performance scores. A higher frequency of METex14 mutations was detected in pulmonary sarcomatoid carcinoma (PSC) patients (24.3%, n = 9/37). However, stage IV PSC patients with or without the METex14 mutations showed similarly poor overall survival (OS) (p = 0.429). For all 36 METex14-positive lung ADCs, multivariate analysis showed several poor prognostic factors, including strong c-MET IHC staining (p = 0.006), initial brain metastasis (p = 0.005), and administration of only supportive care (p &lt; 0.001). After excluding seven patients who received only supportive care, we further analyzed 29 stage IV lung ADC patients with METex14 mutations who received anti-cancer treatment. Multivariate analysis showed that pemetrexed treatment (p = 0.003), lung radiotherapy (p = 0.020), initial brain metastasis (p = 0.005), and strong c-MET IHC staining (p = 0.012) were independent prognostic factors for OS in these patients.

Conclusions

A higher frequency of METex14 mutations was detected in PSC patients. Stage IV PSC patients with or without the METex14 mutations had similarly poor overall survival. Pemetrexed-based chemotherapy, strong c-MET ICH staining, initial brain metastasis, and lung radiotherapy, may help predict survival outcomes in patients with advanced lung ADCs harboring the METex14 mutation.

Survival analysis and individualized prediction of survival benefit for pancreatic signet ring cell carcinoma: a population study based on the SEER database

OBJECTIVES

This study aimed to compare the incidence, clinicopathological characteristics and survival results of pancreatic signet ring cell carcinoma (PSRCC) and pancreatic adenocarcinomas (PDAC), as well as to analyze the clinical characteristics related to the overall survival (OS) of PSRCC, and to establish an effective prognostic nomogram to predict the risks associated with patient outcomes.

METHODS

A total of 85,288 eligible patients including 425 PSRCC and 84,863 PDAC cases were retrieved from the Surveillance, Epidemiology, and End Results database. The survival curve was calculated using the Kaplan-Meier method and differences in them were measured by Log-rank tests. The Cox proportional hazards regression model was used to identify independent predictors of OS in patients with PSRCC. A nomogram was constructed to predict 1-, 3-, and 5-year OS. The performance of the nomogram was measured by C-index, receiver operating characteristic (ROC) curve, decision curve analysis (DCA).

RESULTS

The incidence of PSRCC is much lower than that of PDAC (10.798 V.S. 0.349 per millions). PSRCC is an independent predictor of pancreatic cancer with a poorer histological grade, a higher rate of lymph node and distant metastasis, and a poorer prognosis. We identified four independent prognostic factors including grade, American Joint Committee on Cancer Tumor-Node-Metastasis (TNM) stage, surgery and chemotherapy based on the Cox regression model. The C-index and DCA curves showed better performance of the nomogram than TNM stage. ROC curve analysis also showed that the nomogram had good discrimination, with an area under the curve of 0.840, 0.896, and 0.923 for 1-, 3-, and 5-year survival. The calibration curves showed good agreement between the prediction by the nomogram and actual observations.

CONCLUSION

PSRCC is a rare but fatal subtype of pancreatic cancer. The constructed nomogram in this study accurately predicted the prognosis of PSRCC, performed better than the TNM stage.

Partial response to pralsetinib in an advanced pulmonary sarcomatoid carcinoma patient harboring a KIF5B-RET rearrangement: a case report

BACKGROUND

Pulmonary sarcomatoid carcinoma (PSC) is a rare and unconventional non-small-cell lung cancer (NSCLC) that appears to be aggressive, with a poor prognosis and response to conventional treatment. Approximately 30% of PSCs have potentially targetable genomic alterations, but few studies have involved RET gene fusions, and corresponding targeted therapies are lacking.

CASE PRESENTATION

In this report, we describe a patient with PSC harboring a KIF5B-RET gene fusion who was initially diagnosed with stage IVb lung cancer. Due to the poor performance status, the patient was unable to tolerate any radiotherapy or chemotherapy. Based on the next-generation sequencing (NGS) result of RET gene fusion, the patient was treated with pralsetinib. Two months after the treatment, the patient achieved a partial response.

CONCLUSIONS

Our case indicates that RET is one of the main driver oncogenes of PSC and provides useful information for precise RET inhibitor administration in the future. Thus, the use of comprehensive genomic profiling may provide important treatment options for PSC.

Factors Associated With Lymph Node Yield and Effects of Lymph Node Density on Survival of Patients With Pulmonary Sarcomatoid Carcinoma

OBJECTIVE

The objective of this study was to identify factors associated with lymph node yield (LNY) during surgeries for pulmonary sarcomatoid carcinoma (PSC) and to determine effects of lymph node density (LND) on the overall survival (OS) of patients with PSC.

MATERIALS AND METHODS

The SEER Research Plus database was searched for data on patients with PSC from 1988 to 2018. Poisson regression was used of all patients with PSC to identify relevant factors associated with LNY. Univariate and multivariate Cox regression analyses were adopted for lymph node (LN)-positive patients to evaluate the impact of LND on OS. The 5-year OS rates of patients with PSC were compared based on their LN status and LND.

RESULTS

There were 545 eligible patients in the study sample, 175 of which were LN-positive. These patients had significantly lower 5-year OS than those with no positive LNs ( P <0.001). Poisson regression analysis indicated relevant factors increasing LNY included higher diagnosis age, non-Hispanic American Indian or Alaska Native races, larger tumor, pleomorphic carcinoma histology, and more advanced disease stages. The Cox regression analysis indicated higher LND ( P =0.022) was probably associated with a worse prognosis for LN-positive patients. The group with LND ≥0.12 had a higher risk of death than the group with LND <0.12 ( P <0.001) among LN-positive patients with PSC.

CONCLUSIONS

Patients with PSC with high LND experienced worse outcomes than those with low LND. Further risk stratification of patients with PSC may help to improve survival benefits based on prognostic indicators of LND.

A prediction model for 30-day mortality of sepsis patients based on intravenous fluids and electrolytes

To establish a prediction model for the 30-day mortality in sepsis patients. The data of 1185 sepsis patients were extracted from the Medical Information Mart for Intensive Care III (MIMIC-III) and all participants were randomly divided into the training set (n = 829) and the testing set (n = 356). The model was established in the training set and verified in the testing set. After standardization of the data, age, gender, input, output, and variables with statistical difference between the survival group and the death group in the training set were involved in the extreme gradient boosting (XGBoost) model. Subgroup analysis was performed concerning age and gender in the testing set. In the XGBoost model with variables related to intravenous (IV) fluid management and electrolytes for the 30-day mortality of sepsis patients, the area under the curve (AUC) was 0.868 (95% confidence interval [CI]: 0.867-0.869) in the training set and 0.781 (95% CI: 0.779-0.782) in the testing set. The sensitivity was 0.815 (95% CI: 0.774-0.857) in the training set and 0.755 (95% CI: 0.686-0.825) in the testing set. The specificity was 0.761 (95% CI: 0.723-0.798) in the training set, and 0.737 (95% CI: 0.677-0.797) in the testing set. In the XGBoost forest model without variables related to IV fluid management and electrolytes for the 30-day mortality of sepsis patients, in the training set, the AUC was 0.830 (95% CI: 0.829-0.831), the sensitivity was 0.717 (95% CI: 0.669-0.765), the specificity was 0.797 (95% CI: 0.762-0.833), and the accuracy was 0.765 (95% CI: 0.736-0.794). In the testing set, the AUC was 0.751 (95% CI: 0.750-0.753), the sensitivity was 0.612 (95% CI: 0.533-0.691), the specificity was 0.756 (95% CI: 0.698-0.814), and the accuracy was 0.697(95% CI: 0.649-0.744). The prediction model including variables associated with IV fluids and electrolytes had good predictive value for the 30-day mortality of sepsis patients.

Synchronal pulmonary sarcomatoid carcinoma and lung adenocarcinoma EML4‑ALK fusion: A case report

Pulmonary sarcomatoid carcinoma (PSC) is a rare form of poorly differentiated non-small-cell lung cancer that is prone to distant metastases. PSC is therapeutically challenging, with low sensitivity to conventional radiotherapy and a poor overall prognosis. The present study reported on the case of a 29-year-old male non-smoker diagnosed with both PSC and lung adenocarcinoma; the cancer had a complex etiology and rapidly metastasized after surgery. The patient presented with an EML4-ALK gene fusion in both tumors with high programmed death ligand-1 (PD-L1) expression. After initial treatment failure, Alectinib, Anlotinib and Tirelizumab were combined, which rapidly resolved the patient's symptoms and led to partial remission of disease at 6 weeks and effective control of the disease 7 months into the treatment. This case exemplifies the efficacy of combining targeted chemotherapy with immunotherapy for patients with PSC. Furthermore, this outcome suggests the usefulness of genetic testing and monitoring PD-L1 expression to identify patients with PSC who may be candidates likely to respond to this combined therapeutic regimen. The present study provides evidence of the success of a novel therapeutic strategy for patients with PSC.

PSC subtyping based on TTF-1 and p40 expression reveals distinct molecular characteristics and therapeutic strategies

Pulmonary sarcomatoid carcinoma (PSC) is a unique form of poorly differentiated non-small cell lung cancer (NSCLC) and is notorious for its highly malignant nature and dismal prognosis. To introduce effective treatment for PSC patients, precise subtyping of PSC is demanding. In our study, TTF-1 and P40 immunohistochemistry (IHC) staining were applied to 56 PSC patients with multi-omics data. According to IHC results, we categorized these patients into three subgroups and profiled their molecular contexture using bioinformatic skills. IHC results classified these patients into three subgroups: TTF-1 positive subgroup (n=27), P40 positive subgroup (n=15), and double-negative subgroup (n=14). Spindle cell samples accounted for 35.71% (5/14) of double-negative patients, higher than others (p=0.034). The three subgroups were heterogeneous in the genomic alteration spectrum, showing significant differences in the RTK/RAS pathway (p=0.004) and the cell cycle pathway (p=0.030). The methylation profile of the double-negative subgroup was between the other two subgroups. In similarity analysis, the TTF-1 and p40 subgroups were closely related to LUAD and LUSC, respectively. The TTF-1 positive subgroup had the highest leukocyte fraction (LF) among several cancer types, and the tumor mutation burden (TMB) of the p40 positive subgroup ranked third in the TMB list, suggesting the applicability of immunotherapy for PSC. The study established a new subtyping method of PSC based on IHC results and reveals 3 subgroups with distinct molecular features, providing evidence for refined stratification in the treatment of PSC. This article is protected by copyright. All rights reserved.

Use of PD-1 inhibitor tislelizumab in the treatment of advanced pulmonary sarcomatoid carcinoma: A case report

Pulmonary sarcomatoid carcinoma (PSC), characterized by poor differentiation, aggressive progression, and early metastasis, is a rare type of non‐small cell lung carcinoma (NSCLC), which shows a low response rate to conventional antitumor therapies and has a poor prognosis. With the achievements in gene sequencing, targeted therapy, and immunotherapy, several new approaches have recently been explored in PSC treatment. A small case series of PSC patients were found to have programmed death‐ligand 1 (PD‐L1) overexpression, a prerequisite for PD‐1 inhibiting therapy, which made immunotherapy possible. However, anti‐PD‐1 treatment for PSCs was still at a preliminary stage. Here, we report the successful outcome of tislelizumab monotherapy in a patient with advanced PSC with pleural invasion, thus providing a novel promising approach for PSC patients with PD‐L1 overexpression.

Effect of Marital Status on the Survival of Patients With Adenocarcinoma of the Esophagogastric Junction: A Population-Based, Propensity-Matched Study

Background

Marital status has been reported as an independent prognostic factor in various types of malignancies. However, the association between marital status and outcomes of patients with adenocarcinoma of the esophagogastric junction (AEG) has not been fully explored. To this end, we aimed to investigate the effect of marital status on survival of AGE patients.

Methods

The Surveillance Epidemiology and End Results (SEER) database (2010–2015) was used to extract eligible patients with Siewert type II AEG. Meanwhile, propensity score matching was performed to match 1576 unmarried patients with 1576 married patients. Kaplan–Meier method with log-rank test was used to plot survival curves, univariate and multivariate Cox regression analyses were adopted to investigate the association of marital status with overall survival (OS) and cancer-specific survival (CSS) in AEG patients before and after matching.

Results

Multivariate analysis in the unmatched cohort revealed that marital status was an independent prognostic factor in patients with Siewert type II AEG. Unmarried patients had poorer OS (hazard ratio [HR]: 1.22, 95% confidence interval [CI]: 1.12–1.29, P < .001) and poorer CSS (HR: 1.19, 95% CI: 1.10–1.29, P < .001) than married patients before matching. Additionally, widowed patients had the poorest OS (HR: 1.26, 95% CI: 1.11–1.44, P < .001) and CSS (HR: 1.29, 95% CI: 1.12–1.48, P < .001) compared with married patients. Furthermore, unmarried status remained as an independent prognostic for both OS (HR: 1.20, 95% CI: 1.10–1.31, P < .001) and CSS (HR: 1.18, 95% CI: 1.08–1.30, P < .001) in 1:1 propensity score-matched analysis. Subgroup analysis further revealed that OS and CSS rates were significantly higher in married patients than unmarried ones in most subgroups stratified by different variables.

Conclusions

This population-based study identified that marital status was an independent prognostic indicator for AEG patients. Married AEG patients had better prognosis than their unmarried counterparts.

Prediction of readmission in patients with acute exacerbation of chronic obstructive pulmonary disease within one year after treatment and discharge

Background

To investigate the risk factors and construct a logistic model and an extreme gradient boosting (XGBoost) model to compare the predictive performances for readmission in acute exacerbation of chronic obstructive pulmonary disease (AECOPD) patients within one year.

Methods

In total, 636 patients with AECOPD were recruited and divided into readmission group (n = 449) and non-readmission group (n = 187). Backward stepwise regression method was used to analyze the risk factors for readmission. Data were divided into training set and testing set at a ratio of 7:3. Variables with statistical significance were included in the logistic model and variables with P < 0.1 were included in the XGBoost model, and receiver operator characteristic (ROC) curves were plotted.

Results

Patients with acute exacerbations within the previous 1 year [odds ratio (OR) = 4.086, 95% confidence interval (CI) 2.723–6.133, P < 0.001), long-acting β agonist (LABA) application (OR = 4.550, 95% CI 1.587–13.042, P = 0.005), inhaled corticosteroids (ICS) application (OR = 0.227, 95% CI 0.076–0.672, P = 0.007), glutamic-pyruvic transaminase (ALT) level (OR = 0.985, 95% CI 0.971–0.999, P = 0.042), and total CAT score (OR = 1.091, 95% CI 1.048–1.136, P < 0.001) were associated with the risk of readmission. The AUC value of the logistic model was 0.743 (95% CI 0.692–0.795) in the training set and 0.699 (95% CI 0.617–0.780) in the testing set. The AUC value of XGBoost model was 0.814 (95% CI 0.812–0.815) in the training set and 0.722 (95% CI 0.720–0.725) in the testing set.

Conclusions

The XGBoost model showed a better predictive value in predicting the risk of readmission within one year in the AECOPD patients than the logistic regression model. The findings of our study might help identify patients with a high risk of readmission within one year and provide timely treatment to prevent the reoccurrence of AECOPD.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12890-021-01692-3.