Mining prognostic factors of extensive-stage small-cell lung cancer patients using nomogram model

Prognostic factors in extensive-stage small cell lung cancer patients with organ-specific metastasis: unveiling commonalities and disparities

BACKGROUND

This study aimed to identify shared and distinct prognostic factors related to organ-specific metastases (liver, lung, bone, and brain) in extensive-stage small cell lung cancer (ES-SCLC) patients, then construct nomograms for survival prediction.

METHODS

Patient data for ES-SCLC were from the Surveillance, Epidemiology, and End Results (SEER) database from 2010 to 2019. Kaplan-Meier analysis was applied to estimate overall survival (OS), and Cox regression was used to identify prognostic factors. A Venn diagram was utilized to distinguish common and unique prognostic factors among the variables assessed. These identified prognostic factors were used to formulate a nomogram, and its predictive accuracy and reliability were evaluated using C-indexes, calibration curves, and receiver operating characteristic (ROC) curves.

RESULTS

A total of 24,507 patients diagnosed with ES-SCLC exhibiting metastases to the liver, lung, bone, and brain were included. The 6-month, 1-year, and 2-year OS rates were 46.1%, 19.7%, and 5.0%, respectively. Patients with liver metastasis demonstrated the most unfavorable prognosis, with a 1-year OS rate of 14.5%, while those with brain metastasis had a significantly better prognosis with a 1-year OS rate of 21.6%. The study identified seven common factors associated with a poor prognosis in ES-SCLC patients with organ-specific metastases: older age, male sex, unmarried status, higher T stage, presence of other metastases, and combination radiotherapy and chemotherapy. Furthermore, specific prognostic factors were identified for patients with metastasis to the liver, bone, and brain, including paired tumors, lack of surgical treatment at the primary site, and household income, respectively. To facilitate prognostic predictions, four nomograms were developed and subsequently validated. The performance of these nomograms was assessed using calibration curves, C-indexes, and the area under the curve (AUC), all of which consistently indicated good predictive accuracy and reliability.

CONCLUSIONS

Patients diagnosed with ES-SCLC with organ-specific metastases revealed shared and distinct prognostic factors. The nomograms developed from these factors demonstrated good performance and can serve valuable clinical tools to predict the prognosis of ES-SCLC patients with organ-specific metastases.

Development and validation of prognostic models for small cell lung cancer patients with liver metastasis: a SEER population-based study

BACKGROUND

This study was to establish and validate prediction models to predict the cancer-specific survival (CSS) and overall survival (OS) of small-cell lung cancer (SCLC) patients with liver metastasis.

METHODS

In the retrospective cohort study, SCLC patients with liver metastasis between 2010 and 2015 were retrospectively retrieved from the Surveillance, Epidemiology, and End Results (SEER) database. Patients were randomly divided into the training group and testing group (3: 1 ratio). The Cox proportional hazards model was used to determine the predictive factors for CSS and OS in SCLC with liver metastasis. The prediction models were conducted based on the predictive factors. The performances of the prediction models were evaluated by concordance indexes (C-index), and calibration plots. The clinical value of the models was evaluated by decision curve analysis (DCA).

RESULTS

In total, 8,587 patients were included, with 154 patients experiencing CSS and 154 patients experiencing OS. The median follow-up was 3 months. Age, gender, marital status, N stage, lung metastases, multiple metastases surgery of metastatic site, chemotherapy, and radiotherapy were independent predictive factors for the CSS and OS of SCLC patients with liver metastasis. The prediction models presented good performances of CSS and OS among patients with liver metastasis, with the C-index for CSS being 0.724, whereas the C-index for OS was 0.732, in the training set. The calibration curve showed a high degree of consistency between the actual and predicted CSS and OS. DCA suggested that the prediction models provided greater net clinical benefit to these patients.

CONCLUSION

Our prediction models showed good predictive performance for the CSS and OS among SCLC patients with liver metastasis. Our developed nomograms may help clinicians predict CSS and OS in SCLC patients with liver metastasis.

A review of the utility of prognostic tools in predicting 6-month mortality in cancer patients, conducted in the context of voluntary assisted dying

BACKGROUND

Eligibility to access the Victorian voluntary assisted dying (VAD) legislation requires that people have a prognosis of 6 months or less (or 12 months or less in the setting of a neurodegenerative diagnosis). Yet prognostic determination is frequently inaccurate and prompts clinician discomfort. Based on functional capacity and clinical and biochemical markers, prognostic tools have been developed to increase the accuracy of life expectancy predictions.

AIMS

This review of prognostic tools explores their accuracy to determine 6-month mortality in adults when treated under palliative care with a primary diagnosis of cancer (the diagnosis of a large proportion of people who are requesting VAD).

METHODS

A systematic search of the literature was performed on electronic databases Medline, Embase and Cinahl.

RESULTS

Limitations of prognostication identified include the following: (i) prognostic tools still provide uncertain prognoses; (ii) prognostic tools have greater accuracy predicting shorter prognoses, such as weeks to months, rather than 6 months; and (iii) functionality was often weighted significantly when calculating prognoses. Challenges of prognostication identified include the following: (i) the area under the curve (a value that represents how well a model can distinguish between two outcomes) cannot be directly interpreted clinically and (ii) difficulties exist related to determining appropriate thresholds of accuracy in this context.

CONCLUSIONS

Prognostication is a significant aspect of VAD, and the utility of the currently available prognostic tools appears limited but may prompt discussions about prognosis and alternative means (other than prognostic estimates) to identify those eligible for VAD.

Trends in Epidemiology and Outcome of Small Cell Lung Cancer over 10 Years at Tertiary Cancer Care Center in Iran

Background

Lung cancer is the leading cause of cancer death. Among different lung cancer histopathologies, small cell lung cancer (SCLC) has been known to be the most aggressive and lethal nature. This study analyzed the epidemiological characteristics, outcomes, and trends of SCLC at a tertiary cancer care center in Iran.

Materials and Methods

Retrospectively collected demographic characteristics and survival outcome data on histologically proven SCLC patients during 2009-2019 at the National Research Institute of Tuberculosis and Lung Disease (NRITLD) were reviewed.

Results

In a study of 334 SCLC patients, there were more male patients than female, with a ratio of 2.5 to 1, and the mean age at diagnosis was 58.36 years. While gender distribution and smoking status among women remained consistent over the study period, there was a significant increase in male smokers (P<0.001). Female patients were diagnosed at younger age and had a significantly lower proportion of smokers compared to males (P<0.016). The mean and median overall survival were 10.9 and 8.2 months, with one-, two-, and three-year survival rates of 21%, 10%, and 3% respectively. Younger patients and females had significantly higher survival rates. In both uni/multivariate analyses, only age < 58 years and female gender were significantly associated with longer survival.

Conclusion

The relatively unchanged trend of SCLC in our series suggests that further research on prevention strategies especially smoking cessation, early detection, and new treatment options is urgently required.

Use of radiation therapy among patients with Extensive-stage Small-cell lung cancer receiving Immunotherapy: Canadian consensus recommendations

OBJECTIVES

Thoracic radiation therapy (TRT) and prophylactic cranial irradiation (PCI) are commonly used in the management of extensive-stage small-cell lung cancer (ES-SCLC); however, Phase III trials of first-line immunotherapy often excluded these options. Guidance is needed regarding appropriate use of TRT, PCI, and magnetic resonance imaging (MRI) surveillance while new data are awaited.

MATERIALS AND METHODS

In two web-based meetings, a pan-Canadian expert working group of five radiation oncologists and four medical oncologists addressed eight clinical questions regarding use of radiation therapy (RT) and MRI surveillance among patients with ES-SCLC receiving immunotherapy. A targeted literature review was conducted using PubMed and conference proceedings to identify recent (January 2019-April 2022) publications in this setting. Fifteen recommendations were developed; online voting was conducted to gauge agreement with each recommendation.

RESULTS

After considering recently available evidence across lung cancer populations and clinical experience, the experts recommended that all patients with a response to chemo-immunotherapy, good performance status (PS), and limited metastases be considered for consolidation TRT (e.g., 30 Gy in 10 fractions). When considered appropriate after multidisciplinary team discussion, TRT can be initiated during maintenance immunotherapy. All patients who respond to concurrent chemo-immunotherapy should undergo restaging with brain MRI to guide decision-making regarding PCI versus MRI surveillance alone. MRI surveillance should be conducted for two years after response to initial therapy. PCI (e.g., 25 Gy in 10 fractions or 20 Gy in 5 fractions) can be considered for patients without central nervous system involvement who have a response to chemo-immunotherapy and good PS. Concurrent treatment with PCI and immunotherapy or with TRT, PCI, and immunotherapy is appropriate after completion of initial therapy. All recommendations were agreed upon unanimously.

CONCLUSIONS

These consensus recommendations provide practical guidance regarding appropriate use of RT and immunotherapy in ES-SCLC while awaiting new clinical trial data.

A prognostic nomogram to predict survival in elderly patients with small-cell lung cancer: a large population-based cohort study and external validation

BACKGROUND

Age is an independent prognostic factor for small cell lung cancer (SCLC). We aimed to construct a nomogram survival prediction for elderly SCLC patients based on the Surveillance, Epidemiology, and End Results (SEER) database.

METHODS

A total of 2851 elderly SCLC patients from the SEER database were selected as a primary cohort, which were randomly divided into a training cohort and an internal validation cohort. Additionally, 512 patients from two institutions in China were identified as an external validation cohort. We used univariate and multivariate to determine the independent prognostic factors and establish a nomogram to predict survival. The value of the nomogram was evaluated by calibration plots, concordance index (C-index) and decision curve analysis (DCA).

RESULTS

Ten independent prognostic factors were determined and integrated into the nomogram. Calibration plots showed an ideal agreement between the nomogram predicted and actual observed probability of survival. The C-indexes of the training and validation groups for cancer-specific survival (CSS) (0.757 and 0.756, respectively) based on the nomogram were higher than those of the TNM staging system (0.631 and 0.638, respectively). Improved AUC value and DCA were also obtained in comparison with the TNM model. The risk stratification system can significantly distinguish individuals with different survival risks.

CONCLUSION

We constructed and externally validated a nomogram to predict survival for elderly patients with SCLC. Our novel nomogram outperforms the traditional TNM staging system and provides more accurate prediction for the prognosis of elderly SCLC patients.

Prognostic factors for survival in extensive-stage small cell lung cancer: An Italian real-world retrospective analysis of 244 patients treated over the last decade

BACKGROUND

Potential relationships with the prognosis of patients with extensive-stage non-small cell lung cancer (ES-SCLC) have been investigated without valid results.

METHODS

A retrospective analysis of real-world data of consecutive patients with ES-SCLC admitted to our Medical Thoracic Oncology Unit was carried out from 2010 to 2020, focusing on identification of prognostic factors. Kaplan-Meier analysis was used to represent progression-free survival (PFS) and overall survival (OS). Univariable and multivariable Cox models were used to investigate prognostic factors.

RESULTS

The analysis included 244 patients. The median OS was 8 months (95% confidence interval [CI]: 8-10) and the median PFS was 5 months (95% CI: 5-6). The univariable analysis showed that factors associated with shorter OS were older age (p = 0.047), TNM stage 4 versus 3 (p < 0.001), Eastern Cooperative Oncology Group (ECOG) performance status (PS) 1 and 2 versus 0 (p < 0.001), and >2 metastatic sites (p = 0.004). Mediastinal radiotherapy (RT) (p < 0.001), >1 irradiated site (p = 0.026), 3 and 4 chemotherapy (CT) lines versus 1 (p = 0.044 and 0.001, respectively), prophylactic cranial irradiation (PCI) (p < 0.001), and surgery (p = 0.001) correlated with longer OS. The multivariable analysis revealed statistically significant associations for TNM, ECOG PS 2 versus 0, number of CT lines, PCI, and surgery. A total of 23 patients (9.4%) survived ≥24 months, 39% of whom had received four CT lines and 48% had mediastinal RT.

CONCLUSIONS

Our data suggest that tumor burden, PS, and mediastinal RT strongly correlate with outcome. With the addition of immunotherapy to CT, the identification of new biomarkers as predictive factors is urgently required.

The prognostic risk stratification model for metastatic small-cell lung cancer: An analysis of the SEER database

Distant metastases of small-cell lung cancer (DM-SCLC) is an important factor in the selection of treatment strategies. In this study, we established a nomogram to predict DM-SCLC and determine the benefit of radiotherapy (RT) for DM-SCLC. We analyzed DM-SCLC prognosis based on surveillance, epidemiology, and end result database (SEER) data. A comprehensive and practical nomogram that predicts the overall survival (OS) of DM-SCLC was constructed and the results were compared with the 7th edition of the American Joint Committee on Cancer (AJCC) TNM stage system. A concordance index (C-index) and receiver operating characteristic plot were generated to evaluate the nomogram discrimination. The calibration was evaluated with a calibration plot, and its effectiveness was evaluated by a decision curve analysis (DCA). A score was assigned to each variable, and a total score was established for the risk stratification model. A total of 13,403 DM-SCLC patients were included. Eight characteristic variables were identified as independent prognostic variables. The C-index of the validation and training cohorts was 0.716 and 0.734, respectively. The area under the receiver operating characteristic curve (AUC) values of the nomogram used to predict 1-, 2-, and 3-year OS were 0.751, 0.744, and 0.786 in the validation cohorts (0.761, 0.777, 0.787 in the training cohorts), respectively. The calibration curve of 1-, 2-, 3-year survival rates showed that the prediction of the nomogram was in good agreement with the actual observation. The nomogram exhibited higher clinical utility after evaluation with the 1-, 2-, 3-year DCA compared with the AJCC stage system. A predictive nomogram and risk stratification model have been constructed to evaluate the prognosis of DM-SCLC effectively and accurately. This nomogram may provide a reference for prognosis stratification and treatment decisions.

A nomogram to predict the overall survival of patients with symptomatic extensive-stage small cell lung cancer treated with thoracic radiotherapy

Background

Small cell lung cancer (SCLC) makes up 13% of lung malignancies. Only one-third of SCLC patients received their diagnosis at the limited stage. Treatment for symptomatic extensive-stage (ES) SCLC with persistent intrathoracic disease is still controversial. The present research aimed to analyze the impact of palliative thoracic radiotherapy (TRT) as a treatment for this patient group and build a prognostic nomogram.

Methods

In this retrospective, multi-center study, we analyzed 120 patients with ES-SCLC and a World Health Organization performance status of 1–2 who were diagnosed between March 2014 and September 2019. A nomogram was formulated to predict the patients’ 1- and 2-year overall survival (OS).

Results

The study cohort had a median age of 62 years, and males accounted for 85% of enrollees. A significant extension was observed in the median OS in the TRT group compared to the no TRT group (P<0.001). When the patients were stratified by TRT dose, no significant differences in OS were noted (P=0.530). However, higher levels of inflammatory markers prior to TRT were associated with a shorter OS (neutrophil-to-lymphocyte ratio, P=0.002; platelet/lymphocyte ratio, P=0.023). The nomogram’s Harrell’s concordance (C)-statistic reached 0.70, and the calibration curve analysis revealed goodness of fit.

Conclusions

The neutrophil-to-lymphocyte ratio is an independent factor predicting survival in ES-SCLC patients treated with palliative TRT. Our nomogram, which incorporates immunological markers, has higher accuracy than existing models for the prediction of individuals’ chances of survival, and it could be a significant tool for clinicians in the development of tailored therapeutic strategies.

Development and validation of a nomogram for assessing survival in extensive-stage small-cell lung cancer patients with superior vena cava syndrome referred for thoracic radiotherapy: a comparison of upfront vs. consolidative approaches

PURPOSE

This study sought to design and validate a nomogram capable of predicting outcomes in extensive-stage small-cell lung cancer (ES-SCLC) patients with superior vena cava syndrome (SVCS) based upon the timing of their radiotherapy treatment.

METHODS

We retrospectively analyzed data from 175 ES-SCLC patients with SCVS, comparing outcomes between those that underwent upfront thoracic radiotherapy (initial radiotherapy with simultaneous chemotherapy) and those that underwent consolidative thoracic radiotherapy (following 4-6 cycles of chemotherapy). Significant predictors of patient outcomes were identified using a Cox proportional hazard model and were used to construct our nomogram. This model was subsequently validated using receiver operating characteristic (ROC) curves, concordance index (C-index) values, and a risk classification system in order to evaluate its discriminative and predictive accuracy.

RESULTS

The overall survival (OS) of ES-SCLC patients with SVCS that underwent chemotherapy (CT), consolidative thoracic radiotherapy (cc-TRT), and upfront thoracic radiotherapy (cu-TRT) was 8.2, 11.7, and 14.9 months, respectively (p < 0.001), with respective progression-free survival (PFS) durations of 3.3, 5.0, and 7.3 months (p < 0.001). A multivariate regression analysis revealed age, gender, ECOG performance status, sites of tumor metastasis, and treatment approach to all be independent predictors of survival outcomes. A nomogram was therefore developed incorporating these factors. C‑index values upon internal and external validation of this nomogram were 0.7625 and 0.7959, respectively, and ROC and calibration curves revealed this model to be accurate and consistent.

CONCLUSIONS

We found that upfront thoracic radiotherapy in combination with chemotherapy may be associated with a positive impact on outcomes in ES-SCLC patients with SVCS.