Identifying optimal candidates for primary tumor resection among metastatic non-small cell lung cancer patients: a population-based predictive model

Predicting surgical benefit of primary tumor resection in patients with stage IV colorectal cancer

BACKGROUND

There exists continuous controversy regarding the benefit of primary tumor resection (PTR) for stage IV colorectal cancer (CRC) patients. Little is known about how to predict the patients' benefit from PTR. This study aimed to develop a tool for surgical benefit prediction.

METHODS

Stage IV CRC patients diagnosed between 2010 and 2015 from the Surveillance, Epidemiology and End Results database were included. Patients receiving PTR who survived longer than the median cancer-specific survival (CSS) time of those who did not undergo PTR were considered to benefit from surgery. Logistic regression analysis identified prognostic factors influencing surgical benefit, based on which a nomogram was constructed. The data of patients who underwent PTR from our institution was used for external validation. A user-friendly webserver was then built for convenient clinical use.

RESULTS

The median CSS of the PTR group was 23 months, significantly longer than that of the non-PTR group (7 months, P < 0.001). In the PTR group, 23.3% of patients did not benefit from surgery. Logistic regression analysis identified age, marital status, tumor location, CEA level, chemotherapy, metastasectomy, tumor size, tumor deposits, number of examined lymph nodes, N stage, histological grade and number of distant metastases as independently associated with surgical benefit. The established prognostic nomogram demonstrated satisfactory performance in both the internal and external validation.

CONCLUSION

PTR was associated with prolonged CSS in stage IV CRC. The proposed nomogram could be used as an evidenced-based platform for risk-to-benefit assessment to select appropriate patients for undergoing PTR.

Development and validation of a nomogram for predicting the overall survival in non-small cell lung cancer patients with liver metastasis

Background

Among all metastatic lesions in non-small cell lung cancer (NSCLC), liver metastasis (LM) is the most lethal site with a median survival of less than 5 months. Few studies exclusively report on prognostic factors for these unique patients. We aimed to construct and validate a practical model to predict the prognosis of NSCLC patients with LM.

Methods

Cases of NSCLC with LM diagnosed between 2010 and 2015 were collected from the Surveillance, Epidemiology, and End Results (SEER) database, and were randomly split into training and validation cohort (7:3). The overall survival (OS) was measured from diagnosis until date of death or last follow-up. Cox regression analyses were performed to identify potential predictors of the model. A nomogram incorporating those independent factors was constructed and validated by the concordance index (C-index) and calibration plots. The decision curve analysis (DCA) and a risk stratification system were used to evaluate its clinical value.

Results

A total of 2,367 cases were selected for analysis and randomized to the training cohort (n=1,677) and the validation cohort (n=690). The patients were mainly male (59.3%), married (83.1%) and White (77.3%). Apart from LM, 54.2%, 26.7%, and 36.7% of patients also present with bone, brain, and lung metastases, respectively. The median follow-up was 4.0 months for all patients and 23 months for alive cases. The median OS was 5 months [interquartile range (IQR), 2-11 months]. Sex, age, race, grade, T stage, bone metastasis, brain metastasis, surgery, and chemotherapy were identified as the independent risk factors of the OS and used to develop the nomogram. The calibration curves exhibited excellent agreement between the predicted and actual survival in both the training and validation set, with a C-index of 0.700 [95% confidence interval (CI): 0.684-0.716] and 0.677 (95% CI: 0.653-0.701), respectively. The DCA and the risk classification system further supported that the prediction model was clinically effective.

Conclusions

This is the first study to build a prediction model for NSCLC patients with LM. It aids in treatment decisions, focused care, and physician-patient communication. The global prospective data is needed to further improve this model.

The consideration of surgery on primary lesion of advanced non-small cell lung cancer

BACKGROUND

Numerous reports have shown that medical treatment confers excellent survival benefits to patients with advanced stage IV non-small cell lung cancer (NSCLC). However, the implications of surgery for primary lesions as palliative treatment remain inconclusive.

METHODS

We retrospectively extracted clinical data from the Surveillance, Epidemiology, and End Results Program (SEER) database and selected patients with stage IV NSCLC. Patients were classified into non-surgery and surgery groups, and propensity score matching (PSM) analysis was performed to balance the baseline information. Patients in the surgery group, whose overall survival (OS) was longer than the median survival time of those in the non-surgery group, were deemed to benefit from surgery. We evaluated the efficacy of three surgical techniques, namely, local destruction, sub-lobectomy, and lobectomy, on the primary site in the beneficial population.

RESULTS

The results of Cox regression analyses revealed that surgery was an independent risk factor for both OS (hazard ratio [HR]: 0.441; confidence interval [CI]: 0.426-0.456; P < 0.001) and cancer-specific survival (CSS) (HR: 0397; CI: 0.380-0.414; P < 0.001). Notably, patients who underwent surgery had a better prognosis than those who did not (OS: P < 0.001; CSS: P < 0.001). Moreover, local destruction and sub-lobectomy significantly compromised survival compared to lobectomy in the beneficial group (P < 0.001). After PSM, patients with stage IV disease who underwent lobectomy needed routine mediastinal lymph node clearing (OS: P = 0.0038; CSS: P = 0.039).

CONCLUSION

Based on these findings, we recommend that patients with stage IV NSCLC undergo palliative surgery for the primary site and that lobectomy plus lymph node resection should be conventionally performed on those who can tolerate the surgery.

Identified optimal candidates for pulmonary resection in octogenarians with non-small cell lung cancer: a web-based predictive model

Background

A survival benefit from pulmonary resection was observed in octogenarians with non-small cell lung cancer (NSCLC). Meanwhile, the identification of patients who can indeed benefit can be difficult. Therefore, we aimed to establish a web-based predictive model to identify optimal candidates for pulmonary resection.

Methods

Octogenarians with NSCLC in Surveillance, Epidemiology and End Results (SEER) database were enrolled and split into the surgery and non-surgery groups based on whether they received pulmonary resection. Propensity-score matching (PSM) was utilized to eliminate the imbalance. Independent prognostic factors were identified. Patients in the surgery group who lived longer than the median cancer-specific survival (CSS) time of the non-surgery group were assumed to benefit from the surgery. The surgery group was further divided into the beneficial group and the non-beneficial group based on the median CSS time of the non-surgery group. Among the surgery group, a nomogram was established through a logistic regression model.

Results

A total of 14,264 eligible patients were extracted, with 4,475 (31.37%) patients receiving pulmonary resection. Surgery was an independent favorable factor of prognosis after PSM (median CSS time: 58 vs. 14 months, P<0.001). A total of 750 (70.4%) patients lived longer than 14 months (beneficial group) in the surgery group. Factors including age, gender, race, histologic type, differentiation grade, and tumor-node-metastasis (TNM) stage were used to formulate the web-based nomogram. The precise discrimination and predictive capability of the model were validated through receiver operating characteristic curves, calibration plots, and decision curve analyses.

Conclusions

A web-based predicted model was constructed to distinguish specific patients who can indeed benefit from pulmonary resection among octogenarians with NSCLC.

Development of a predictive model to identify patients most likely to benefit from surgery in metastatic breast cancer

Primary tumor resection for metastatic breast cancer (MBC) has demonstrated a survival advantage, however, not all patients with MBC benefit from surgery. The purpose of this study was to develop a predictive model to select patients with MBC who are most likely to benefit from surgery at the primary site. Data from patients with MBC were obtained from the Surveillance, Epidemiology and End Results (SEER) cohort and patients treated at the Yunnan Cancer Hospital. The patients from the SEER database were divided into surgery and non-surgery groups and a 1:1 propensity score matching (PSM) was used to balance baseline characteristics. We hypothesized that patients who underwent local resection of primary tumors had improved overall survival (OS) compared to those who did not undergo surgery. Based on the median OS time of the non-surgery group, patients from the surgery group were further categorized into beneficial and non-beneficial groups. Logistic regression analysis was performed to identify independent factors associated with improved survival in the surgery group and a nomogram was established using the most significant predictive factors. Finally, internal and external validation of the prognostic nomogram was also evaluated by concordance index (C-index) and using a calibration curve. A total of 7759 eligible patients with MBC were identified in the SEER cohort and 92 with MBC patients who underwent surgery at the Yunnan Cancer Hospital. Amongst the SEER cohort, 3199 (41.23%) patients received surgery of the primary tumor. After PSM, the OS between the surgery and non-surgery group was significantly different based on Kaplan-Meier survival analysis (46 vs. 31 months, P < 0.001), In the surgery group, 562 (55.20%) patients survived for longer than 31 months and were classified in the beneficial group. Significant differences were observed in patient characteristics between the beneficial and non-beneficial groups including age, grade, tumor size, liver metastasis, breast cancer subtype and marital status. These factors were used as independent predictors to create a nomogram. The internally and externally validated C-indices of the nomogram were 0.703 and 0.733, respectively, indicating strong consistency between the actual and predicted survival. A nomogram was developed and used to identify MBC patients who are most likely to benefit from primary tumor resection. This predictive model has the potential to improve clinical decision-making and should be considered routine clinical practice.

Construction, validation and, visualization of a web-based nomogram to identify the best candidates for primary tumor resection in advanced cutaneous melanoma patients

Background

Existing studies have shown whether primary site resection (PSR) in cutaneous melanoma (CM) patients with stage IV is controversial. Our study aimed to identify the clinical characteristics of CM patients with stage IV who benefited from PSR on a population-based study.

Methods

We retrospectively reviewed stage IV CM patients in the Surveillance, Epidemiology, and End Results (SEER) database from 2004 to 2015. Patients were divided into surgical and non-surgical groups according to whether PSR was performed or not. According to the median cancer-specific survival (CSS) time of the non-surgery group, the surgical group was divided into the surgery-benefit group and the non-surgery-benefit group. Multivariate cox regression analysis was used to explore independent CSS prognostic factors in the surgical group. Then, based on the independent prognostic factors of the surgical group, we established a web-based nomogram based on logistics regression.

Results

A total of 574 stage IV CM patients were included in our study, and 491 (85.60%) patients were included in the surgical group. The clinical characteristics (benefit group and non-benefit group) included age, M stage, lesion location, and ulceration status. These independent prognostic factors were includeed to construct a web-based nomogram.

Conclusions

We constructed a web-based nomogram. This model was suitable for identifying the best candidates suitable for PSR in stage IV CM patients.

Predicting Surgical Benefit for Primary Tumor Resection in Patients with Stage IV Colorectal Cancer.. [DOI: 10.21203/rs.3.rs-2031087/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

Purpose There exists continuous controversy regarding the effect of primary tumor resection (PTR) for stage IV colorectal cancer (CRC) patients. Little is known about how to predict the patients’ survival benefit from PTR. This study aimed to develop a tool for surgical benefit prediction. Methods Stage IV CRC patients diagnosed between 2010 and 2015 from the Surveillance, Epidemiology, and End Results database were included. After propensity score matching, patients receiving PTR that survived longer than the median cancer-specific survival (CSS) time of those who did not undergo PTR were considered to benefit from surgery. Logistic regression analysis identified prognostic factors influencing the surgical benefit, based on which a nomogram was constructed. A user-friendly webserver was then built for convenient clinical use. The predictive model was assessed using Harrell’s concordance index, calibration plot, receiver operative curve and decision curve analysis. Results The median CSS of the PTR group was 23 months, which was significantly longer than the non-PTR group (12 months, P < 0.001). In the PTR group, 32.9% of patients did not benefit from surgery. Logistic regression analysis identified age, tumor location, CEA level, histological grade, number of distant metastasis, and preoperative chemotherapy independently associated with surgical benefit. The established prognostic nomogram demonstrated satisfactory performance. Conclusion PTR was associated with prolonged survival in stage IV CRC. The proposed nomogram could be used as a risk-to-benefit assessment evidenced-based platform for selecting appropriate patients to undergo PTR.

The Prognostic Impact of Lymph Node Dissection on Primary Tumor Resection for Stage IV Non-Small Cell Lung Cancer: A Population-Based Study

Objective

Selected patients with stage IV non–small cell lung cancer (NSCLC) who underwent primary tumor resection have witnessed a survival benefit. Whether additional lymph node dissection (LND) would result in a better effect remain unknown. We investigated the prognostic impact of LND on patients with stage IV NSCLC who received primary tumor resection (PTR).

Methods

Patients with stage IV NSCLC who underwent PTR were identified from the Surveillance, Epidemiology, and End Results database from 2004 to 2016. Propensity-score matching was performed to minimize the confounding effect, and lung cancer-specific survival (CSS) and overall survival (OS) were compared after matching. Multivariable Cox regression was used to identify prognostic factors and to adjust for covariates in subgroup analysis. The effect of the number of lymph nodes examined on the CSS was evaluated by repeating the Cox analysis in a binary method.

Results

A total of 4,114 patients with stage IV NSCLC who receive surgery met our criteria, of which 2,622 (63.73%) underwent LND and 628 patients were identified 1:1 in LND and non-LND groups after matching. Compared with the non-LND group, the LND group had a longer CSS (median: 23 vs. 16 months, p < 0.001) and OS (median: 21 vs. 15 months, p < 0.001). Multivariable regression showed that LND was independently associated with favorable CCS [hazard ratio (HR) = 0.78, 95% confidence interval (CI) 0.69–0.89, P < 0.001] and OS (HR = 0.79, 95% CI 0.70–0.89, P < 0.001). Subgroup analysis suggested that LND is an independent favorable predictor to survival in the surgical patients who were older age (>60 years old), female, T3-4, N0, and M1a stage and those who underwent sublobar resection. In addition, a statistically significant CCS benefit was associated with an increasing number of lymph nodes examined through 25 lymph nodes.

Conclusions

LND with a certain range of lymph nodes number examined was associated with improved survival for patients with stage IV NSCLC who received primary tumor resection. The results may have implications for guidelines on lymph nodes management in selective advanced NSCLC for surgery.

Construction and validation of prognostic nomograms for elderly patients with metastatic non-small cell lung cancer

BACKGROUND

Metastatic non-small cell lung cancer (NSCLC) is mostly seen in older patients and is associated with poor prognosis. There is no reliable method to predict the prognosis of elderly patients (≥60 years old) with metastatic NSCLC. The aim of our study was to develop and validate nomograms which accurately predict survival in this group of patients.

METHODS

NSCLC patients diagnosed between 2010 and 2015 were all identified from the Surveillance, Epidemiology, and End Results (SEER) database. Nomograms were constructed by significant clinicopathological variables (p < 0.05) selected in multivariate Cox analysis regression.

RESULTS

A total of 9584 patients met the inclusion criteria and were randomly allocated in the training (n = 6712) and validation (n = 2872) cohorts. In training cohort, independent prognostic factors included age, gender, race, grade, tumor site, pathology, T stage, N stage, radiotherapy, surgery, chemotherapy, and metastatic site (p < 0.05) for lung cancer-specific survival (LCSS) and overall survival (OS) were identified by the Cox regression. Nomograms for predicting 1-, 2-, and 3-years LCSS and OS were established and showed excellent predictive performance with a higher C-index than that of the 7th TNM staging system (LCSS: training cohort: 0.712 vs. 0.534; p < 0.001; validation cohort: 0.707 vs. 0.528; p < 0.001; OS: training cohort: 0.713 vs. 0.531; p < 0.001; validation cohort: 0.710 vs. 0.528; p < 0.001). The calibration plots showed good consistency from the predicted to actual survival probabilities both in training cohort and validation cohort. Moreover, the decision curve analysis (DCA) achieved better net clinical benefit compared with TNM staging models.

CONCLUSIONS

We established and validated novel nomograms for predicting LCSS and OS in elderly patients with metastatic NSCLC with desirable discrimination and calibration ability. These nomograms could provide personalized risk assessment for these patients and assist in clinical decision.

A Model for Identifying Optimal Patients for Primary Tumor Resection in Patients With Metastatic Bladder Cancer

Background

A survival benefit was observed in metastatic bladder cancer patients who underwent primary tumor resection, but it was still confusing which patients are suitable for the surgery. For this purpose, we developed a model to screen stage M1 patients who would benefit from primary tumor resection.

Methods

Patients with metastatic bladder cancer were screened from the Surveillance, Epidemiology, and End Results database (2004–2016) and then were divided into surgery (partial or complete cystectomy) group and non-surgery group. To balance the characteristics between them, a 1:1 propensity score matching analysis was applied. A hypothesis was proposed that the received primary tumor resection group has a more optimistic prognosis than the other group. The multivariable Cox model was used to explore the independent factors of survival time in two groups (beneficial and non-beneficial groups). Logistic regression was used to build a nomogram based on the significant predictive factors. Finally, a variety of methods are used to evaluate our model.

Results

A total of 7,965 patients with metastatic bladder cancer were included. And 3,314 patients met filtering standards, of which 545 (16.4%) received partial or complete cystectomy. Plots of the Kaplan–Meier and subgroup analyses confirmed our hypothesis. After propensity score matching analysis, a survival benefit was still observed that the surgery group has a longer median overall survival time (11.0 vs. 6.0 months, p < 0.001). Among the surgery cohort, 303 (65.8%) patients lived longer than 6 months (beneficial group). Differentiated characteristics included age, gender, TNM stage, histologic type, differentiation grade, and therapy, which were integrated as predictors to build a nomogram. The nomogram showed good discrimination in both training and validation cohorts (area under the receiver operating characteristic curve (AUC): 0.806 and 0.742, respectively), and the calibration curves demonstrated good consistency. Decision curve analysis showed that the nomogram was clinically useful. Compared with TNM staging, our model shows a better predictive value in identifying optimal patients for primary tumor resection.

Conclusions

A practical predictive model was created and verified, which might be used to identify the optimal candidates for the partial or complete cystectomy group of the primary tumor among metastatic bladder cancer.

Distinguishing optimal esophagectomy candidates in elderly patients: A nomogram based on propensity score matching

BACKGROUND

A survival benefit from esophagectomy was observed in elderly patients. But it's unclear how to identify specific patients who can benefit. Thus, we aimed to establish a predictive model to identify optimal candidates for esophagectomy.

METHODS

Patients (age ≥75 years) with esophageal cancer in Surveillance, Epidemiology and End Results (SEER) database were used to establish the predictive model. Propensity-score matching (PSM) was applied to eliminate the imbalance between esophagectomy group and non-esophagectomy group. We hypothesized that elderly patients could benefit from esophagectomy with longer cancer specific survival (CSS) time than those who did not receive esophagectomy. Patients received surgery were divided into beneficial group and non-beneficial group according to the median CSS time of non-esophagectomy group. Prognostic factors affecting patients' long-term survival were identified. Among esophagectomy group, a logistic regression model based on these factors was established to build a nomogram.

RESULTS

A total of 7,025 eligible patients were extracted from the SEER database, with 831 patients received esophagectomy. Surgery was independently associated with better long-term survival (median CSS time in the matched population: 35 vs. 8 months, p < 0.001). As a result, 361 (68.6%) patients were divided into beneficial group (CSS >8 months). Factors including age, tumor site, histology, differentiation grade, TNM stage, and tumor size were used to formulate the nomogram, which was named as esophagectomy candidates screening score (ECSS). The validation from two aspects showed the model a useful and stable one.

CONCLUSION

A predictive model was established to distinguish optimal candidates for esophagectomy among elderly patients with EC.

Short-term response might influence the treatment-related benefit of adjuvant chemotherapy after concurrent chemoradiotherapy for esophageal squamous cell carcinoma patients

BACKGROUND

Whether adjuvant chemotherapy (AC) after concurrent chemoradiotherapy (CCRT) could provide benefit to esophageal squamous cell carcinoma (ESCC) patients is controversial. Therefore, we decided to investigate the potential benefit of AC after CCRT for ESCC and to identify biomarkers predictive of a clinical benefit.

METHODS

We retrospectively analysed the clinical data of ESCC patients with clinical stage II-IVa who underwent CCRT. Then, we compared patients who received CCRT and AC (CCRT + AC group) with those who received CCRT alone (CCRT group). Propensity score analysis, subgroup analysis and an additional Cox regression model were conducted to analyse the predictive factors. The overall survival (OS) and progression-free survival (PFS) rates were taken as the endpoints.

RESULTS

From January 2013 to December 2017, 244 patients were recruited (n = 131 for CCRT + AC; n = 113 for CCRT alone) for the analysis. After propensity score matching was performed (1:1 and 99 patients for each group) with consideration of the basic clinical characteristics, no significant differences were found in OS (HR = 1.024; 95% CI 0.737-1.423; P = 0.886) or PFS (HR = 0.809; 95% CI 0.582-1.126; P = 0.197) between the two groups. The good short-term response subgroup showed a better PFS and favoured CCRT + AC treatment (HR = 0.542; 95% CI 0.336-0.876; P = 0.008), the independent predictive role of which was confirmed in additional multivariate Cox regression analysis.

CONCLUSIONS

Although AC did not significantly improve PFS and OS for all ESCC patients after CCRT, the short-term response to CCRT might help identify a subgroup that will benefit, which needs further prospective research to confirm.

Surgery for advanced-stage non-small cell lung cancer: lobectomy or sub-lobar resection?

Background

Metastatic non-small cell lung cancer (NSCLC) has many comorbidities, such as chronic obstructive pulmonary disease, coronary heart disease, and older age-related comorbidities. A survival benefit was observed in such patients who underwent surgery for selected oligometastatic disease. However, to the best of our knowledge, there is no evidence to support whether lobectomy (compared with sub-lobar resection) would further prolong these patients' lives.

Methods

Patients with metastatic NSCLC who underwent primary tumor resection were identified from the Surveillance, Epidemiology, and End Results (SEER) database and then divided into lobectomy and sub-lobar resection groups. Propensity score matching (PSM, 1:1) was performed to match the baseline characteristics of the two groups. Cancer-specific survival (CSS) was estimated.

Results

In total, 24,268 patients with metastatic NSCLC were identified; 4,114 (16.95%) underwent primary tumor surgery, and of these, 2,045 (49.71%) underwent lobectomy and 1,766 (42.93%) underwent sub-lobar resection. After PSM, 644 patients in each group were included. Lobectomy was independently correlated with longer median CSS time [hazards ratio (HR): 0.70, 95% confidence interval (CI): 0.61-0.80, P<0.001]. The 1, 2, and 3-year survival rates after PSM also favored the lobectomy group. However, no significant survival difference was found for wedge resection and segmentectomy (HR: 0.96, 95% CI: 0.70-1.31, P=0.490). The 1-, 2-, and 3-year survival rates after PSM also exhibited no difference within the sub-lobar group. We explored whether lymph node dissection would provide additional survival benefits for stage IV NSCLC patients. According to the multivariate Cox analysis of the matched population, lymph node dissection was independently associated with better CSS (HR: 0.76, 95% CI: 0.66-0.88, P<0.001) and overall survival (OS) (HR: 0.74, 95% CI: 0.65-0.86, P<0.001). We confirmed this result in the different types of surgery and found that the lymph node dissection group consistently had better survival outcomes both in the lobectomy group and sub-lobar resection population. According to the subgroup analysis, with the exception of stage T4 and brain metastatic patients, all of the patient subtypes exhibited greater benefit from lobectomy than sub-lobar resection.

Conclusions

Lobectomy has a greater survival benefit in metastatic NSCLC patients compared with sub-lobar resection when radical treatment of primary site was indicated.