A nomogram for predicting survival of patients with locally advanced pancreatic cancer treated with chemoradiotherapy

Minimum and Optimal CA19-9 Response After Two Months Induction Chemotherapy in Patients With Locally Advanced Pancreatic Cancer: A Nationwide Multicenter Study

OBJECTIVE

This nationwide multicenter study aimed to define clinically relevant thresholds of relative serum CA19-9 response after 2 months of induction chemotherapy in patients with locally advanced pancreatic cancer (LAPC).

BACKGROUND

CA19-9 is seen as leading biomarker for response evaluation in patients with LAPC, but early clinically useful cut-offs are lacking.

METHODS

All consecutive patients with LAPC after 4 cycles (m)FOLFIRINOX or 2 cycles gemcitabine-nab-paclitaxel induction chemotherapy (±radiotherapy) with CA19-9 ≥5 U/mL at baseline were analyzed (2015-2019). The association of CA19-9 response with median OS (mOS) was evaluated for different CA19-9 cut-off points. Minimum and optimal CA19-9 response were established via log-rank test. Predictors for OS were analyzed using COX regression analysis.

RESULTS

Overall, 212 patients were included, of whom 42 (19.8%) underwent resection. Minimum CA19-9 response demonstrating a clinically significant median OS difference (12.7 vs. 19.6 months) was seen at ≥40% CA19-9 decrease. The optimal cutoff for CA19-9 response was ≥60% decrease (21.7 vs. 14.0 mo, P =0.021). Only for patients with elevated CA19-9 levels at baseline (n=184), CA19-9 decrease ≥60% [hazard ratio (HR)=0.59, 95% CI, 0.36-0.98, P =0.042] was independently associated with prolonged OS, as were SBRT (HR=0.42, 95% CI, 0.25-0.70; P =0.001), and resection (HR=0.25, 95% CI, 0.14-0.46, P <0.001), and duration of chemotherapy (HR=0.75, 95% CI, 0.69-0.82, P <0.001).

CONCLUSIONS

CA19-9 decrease of ≥60% following induction chemotherapy as optimal response cut-off in patients with LAPC is an independent predictor for OS when CA19-9 is increased at baseline. Furthermore, ≥40% is the minimum cut-off demonstrating survival benefit. These cut-offs may be used when discussing treatment strategies during early response evaluation.

Preoperative chemotherapy, radiotherapy and surgical decision-making in patients with borderline resectable and locally advanced pancreatic cancer

Surgical resection combined with systemic chemotherapy is the cornerstone of treatment for patients with localized pancreatic cancer. Upfront surgery is considered suboptimal in cases with extensive vascular involvement, which can be classified as either borderline resectable pancreatic cancer or locally advanced pancreatic cancer. In these patients, FOLFIRINOX or gemcitabine plus nab-paclitaxel chemotherapy is currently used as preoperative chemotherapy and is eventually combined with radiotherapy. Thus, more patients might reach 5-year overall survival. Patient selection for chemotherapy, radiotherapy and subsequent surgery is based on anatomical, biological and conditional parameters. Current guidelines and clinical practices vary considerably regarding preoperative chemotherapy and radiotherapy, response evaluation, and indications for surgery. In this Review, we provide an overview of the clinical evidence regarding disease staging, preoperative therapy, response evaluation and surgery in patients with borderline resectable pancreatic cancer or locally advanced pancreatic cancer. In addition, a clinical work-up is proposed based on the available evidence and guidelines. We identify knowledge gaps and outline a proposed research agenda.

Prognostic models to predict survival in patients with pancreatic cancer: a systematic review

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) has poor survival. Current treatments offer little likelihood of cure or long-term survival. This systematic review evaluates prognostic models predicting overall survival in patients diagnosed with PDAC.

METHODS

We conducted a comprehensive search of eight electronic databases from their date of inception through to December 2019. Studies that published models predicting survival in patients with PDAC were identified.

RESULTS

3297 studies were identified; 187 full-text articles were retrieved and 54 studies of 49 unique prognostic models were included. Of these, 28 (57.1%) were conducted in patients with advanced disease, 17 (34.7%) with resectable disease, and four (8.2%) in all patients. 34 (69.4%) models were validated, and 35 (71.4%) reported model discrimination, with only five models reporting values >0.70 in both derivation and validation cohorts. Many (n = 27) had a moderate to high risk of bias and most (n = 33) were developed using retrospective data. No variables were unanimously found to be predictive of survival when included in more than one study.

CONCLUSION

Most prognostic models were developed using retrospective data and performed poorly. Future research should validate instruments performing well locally in international cohorts and investigate other potential predictors of survival.

Nomogram to predict survival of patients with advanced and metastatic pancreatic Cancer

BACKGROUND

Nomograms are rarely employed to estimate the survival of patients with advanced and metastatic pancreatic cancer (PC). Herein, we developed a comprehensive approach to using a nomogram to predict survival probability in patients with advanced and metastatic PC.

METHODS

A total of 323 patients with advanced and metastatic PC were identified from the Chinese People's Liberation Army (PLA) General Hospital. A baseline nomogram was constructed using baseline variables of 323 patients. Additionally, 233 patients, whose tumors showed initial responses to first-line chemotherapy, were enrolled in the chemotherapy response-based model. 128 patients and 108 patients with advanced and metastatic PC from January 2019 to April 2021 were selected for external validating baseline model and chemotherapy response-based model. The 1-year and 2-year survival probability was evaluated using multivariate COX regression models. The discrimination and calibration capacity of the nomograms were assessed using C-statistic and calibration plots. The predictive accuracy and net benefit of the nomograms were evaluated using ROC curve and DCA, respectively.

RESULTS

In the baseline model, six variables (gender, KPS, baseline TB, baseline N, baseline WBC and baseline CA19-9) were used in the final model. In the chemotherapy response-based model, nine variables (KPS, gender, ascites, baseline N, baseline CA 19-9, baseline CEA, change in CA 19-9 level at week, change in CEA level at week and initial response to chemotherapy) were included in the final model. The C-statistics of the baseline nomogram and the chemotherapy response-based nomogram were 0.67 (95% CI, 0.62-0.71) and 0.74 (95% CI, 0.69-0.77), respectively.

CONCLUSION

These nomograms were constructed to predict the survival probability of patients of advanced and metastatic PC. The baseline model and chemotherapy response-based model performed well in survival prediction.

Identification of DNA methylation-driven genes and construction of a nomogram to predict overall survival in pancreatic cancer

Background

The incidence and mortality of pancreatic cancer (PC) has gradually increased. The aim of this study was to identify survival-related DNA methylation (DNAm)-driven genes and establish a nomogram to predict outcomes in patients with PC.

Methods

The gene expression, DNA methylation database, and PC clinical samples were downloaded from TCGA. DNAm-driven genes were identified by integrating analyses of gene expression and DNA methylation data. Survival-related DNAm-driven genes were screened via univariate, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analyses to develop a risk score model for prognosis. Based on analyses of clinical parameters and risk score, a nomogram was built and validated. The independent cohort from GEO database were used for external validation.

Results

A total of 16 differentially expressed methylation-driven genes were identified. Based on LASSO Cox regression and multivariate Cox regression analysis, six genes (FERMT1, LIPH, LAMA3, PPP1R14D, NQO1, VSIG2) were chosen to develop the risk score model. In the Kaplan–Meier analysis, age, T stage, N stage, AJCC stage, radiation therapy history, tumor size, surgery type performed, pathological type, chemotherapy history, and risk score were potential prognostic factors in PC (P < 0.1). In the multivariate analysis, stage, chemotherapy, and risk score were significantly correlated to overall survival (P < 0.05). The nomogram was constructed with the three variables (stage, chemotherapy, and risk score) for predicting the 1-year, 2-year, and 3-year survival rates of PC patients. Nomogram performance was assessed by receiver operating characteristic (ROC) curves and calibration curves. 1-year, 2-year and 3-year AUC of nomogram model was 0.899, 0.765 and 0.776, respectively.

Conclusions

In our study, we successfully identified the six DNAm-driven genes (FERMT1, LIPH, LAMA3, PPP1R14D, NQO1, VSIG2) with a relationship to the outcomes of PC patients. The nomogram including stage, chemotherapy, and risk score could be used to predict survival in PC patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-08097-w.

The Prognostic Significance of Novel Pancreas Cancer Prognostic Index in Unresectable Locally Advanced Pancreas Cancers Treated with Definitive Concurrent Chemoradiotherapy

Purpose

We evaluated the prognostic quality of the novel pancreas cancer prognostic index (PCPI), a combination of CA 19-9 and systemic inflammation response index (SIRI), on the outcomes of locally advanced pancreas adenocarcinoma (LAPAC) patients who received concurrent chemoradiotherapy (C-CRT).

Methods

This retrospective analysis covered 152 unresectable LAPAC patients treated from 2007 to 2019. Receiver operating characteristic (ROC) curve analysis was used to define ideal cutoff thresholds for the pretreatment CA 19-9 and SIRI measurements, individually. The associations between the PCPI groups and progression-free- (PFS) and overall survival (OS) comprised the respective primary and secondary endpoints.

Results

The ROC curve analysis distinguished the respective rounded optimal cutoffs at 91 U/m/L (< versus ≥90) and 1.8 (< versus ≥1.8) for CA 19-9 and SIRI, arranging the study cohort into two significantly different survival groups for each, with resultant four likely groups: Group-1: CA 19-9<90 U/m/L and SIRI<1.8, Group-2: CA 19-9<90 U/m/L but SIRI≥1.8, Group-3: CA 19-9≥90 U/m/L but SIRI<1.8, and Group-4: CA 19-9≥90 U/m/L and SIRI≥1.8. Since the PFS (P=0.79) and OS (P=0.86) estimates of the groups 2 and 3 were statistically indistinct, we merged them as one group and created the novel three-tiered PCPI: PCPI-1: CA 19-9<90 U/m/L and SIRI<1.8, PCPI-2: CA 19-9<90 U/m/L but SIRI≥1.8 or CA 19-9≥90 U/m/L but SIRI<1.8, and PCPI-3: CA 19-9≥90 U/m/L and SIRI≥1.8, respectively. Comparative analyses unveiled that the PCPI-1 and PCPI-3 groups had the respective best and worst PFS (17.0 versus 7.5 versus 4.4 months; P<0.001) and OS (26.1 versus 15.1 versus 7.4 months; P<0.001) outcomes, while the PCPI-2 group posed in between. The multivariate analysis outcomes confirmed the novel three tired PCPI’s independent prognostic significance on either of the PFS [HR: 5.38 (95% confidence interval (CI): 4.96-5.80); P<0.001)] and OS [HR: 5.67 (95% CI: 5.19-6.15); P<0.001] endpoints, separately.

Conclusion

The new PCPI introduced here can be used as an independent and reliable prognostic indicator to divide LAPAC patients into three subgroups with discrete survival results.

Prognostic nomogram for hepatocellular carcinoma with radiofrequency ablation: a retrospective cohort study

Background

Radiofrequency ablation (RFA) is an effective treatment option for hepatocellular carcinoma (HCC). This study aimed to analyze the prognostic factors of HCC patients treated with RFA and to develop nomograms for outcome prediction.

Methods

A total of 3142 HCC patients treated with RFA were recruited, and their data were collected from the Surveillance, Epidemiology, and End Results database. Univariate and multifactor Cox analyses were performed to identify independent prognostic factors. These factors were integrated into a nomogram to predict 3- and 5-year cancer-specific survival (CSS) and overall survival (OS). Consistency indices and calibration plots were used to assess the accuracy of the nomograms in both the internal and external cohorts.

Results

The median follow-up periods for HCC patients treated with RFA were 27 and 29 months for OS and CSS, respectively. Marital status, age, race, histological grade of differentiation, tumor size, T stage, and serum alpha-fetoprotein levels at the time of diagnosis were identified as prognostic factors for OS and CSS. Additionally, M stage was identified as risk factors for OS. These risk factors are included in the nomogram. The calibration plots of the OS and CSS nomograms showed excellent consistency between actual survival and nomogram predictions. The bootstrap-corrected concordance indices of the OS and CSS nomograms were 0.637 (95% CI, 0.628–0.646) and 0.670 (95% 0.661–0.679), respectively. Importantly, our nomogram performed better discriminatory compared with 8th edition tumor-node-metastasis (TNM) stage system for predicting OS and CSS.

Conclusions

We identified prognostic factors for HCC patients treated with RFA and provided an accurate and personalized survival prediction scheme.

Predicting overall survival and resection in patients with locally advanced pancreatic cancer treated with FOLFIRINOX: Development and internal validation of two nomograms

BACKGROUND AND OBJECTIVES

Patients with locally advanced pancreatic cancer (LAPC) are increasingly treated with FOLFIRINOX, resulting in improved survival and resection of tumors that were initially unresectable. It remains unclear, however, which specific patients benefit from FOLFIRINOX. Two nomograms were developed predicting overall survival (OS) and resection at the start of FOLFIRINOX for LAPC.

METHODS

From our multicenter, prospective LAPC registry in 14 Dutch hospitals, LAPC patients starting first-line FOLFIRINOX (April 2015-December 2017) were included. Stepwise backward selection according to the Akaike Information Criterion was used to identify independent baseline predictors for OS and resection. Two prognostic nomograms were generated.

RESULTS

A total of 252 patients were included, with a median OS of 14 months. Thirty-two patients (13%) underwent resection, with a median OS of 23 months. Older age, female sex, Charlson Comorbidity Index ≤1, and CA 19.9 < 274 were independent factors predicting a better OS (c-index: 0.61). WHO ps >1, involvement of the superior mesenteric artery, celiac trunk, and superior mesenteric vein ≥ 270° were independent factors decreasing the probability of resection (c-index: 0.79).

CONCLUSIONS

Two nomograms were developed to predict OS and resection in patients with LAPC before starting treatment with FOLFIRINOX. These nomograms could be beneficial in the shared decision-making process and counseling of these patients.

Development and Validation of Multicenter Predictive Nomograms for Locally Advanced Pancreatic Cancer After Chemoradiotherapy

Objective

Due to common practice of hypofractionated radiotherapy in pancreatic cancer and heterogeneous chemotherapy regimens in previous studies, modified nomograms are required. Therefore, we aim to develop and validate prognostic nomograms for locally advanced pancreatic cancer (LAPC) after stereotactic body radiation therapy (SBRT) and chemotherapy.

Methods

The development cohort comprised 925 patients with LAPC receiving SBRT and gemcitabine-based chemotherapy in our center, while 297 patients from another two centers formed the validation cohort. Nomograms were created from COX models and internally validated by bootstrap. Model discriminations were evaluated by calibration plots and concordance index (C-index). A decision curve analysis (DCA) was performed to evaluate clinical benefits of nomograms. Additionally, recursive partitioning analysis (RPA) was used for stratifications of survival probability based on the total score of each patient calculated by nomograms.

Results

Weight loss, tumor diameter, radiation dose, CA19-9 kinetics after treatment and surgical resection were included in the nomogram for overall survival (OS), while the five factors plus performance status formed the nomogram for progression free survival (PFS). The corrected C-indexes for estimated 1-year and 2-year OS of the development cohort were 0.88 (95% CI: 0.85-0.91) and 0.86 (95% CI: 0.83-0.90). For those of the validation cohort, it was 0.88 (95% CI: 0.82-0.94) and 0.83 (95% CI: 0.74-0.91). Additionally, the corrected C-index for predicted 1-year PFS in the development and validation cohort was 0.83 (95% CI: 0.81-0.86) and 0.82 (95% CI: 0.78-0.87), respectively. The calibration plots showed good agreement of 1- and 2-year OS and 1-year PFS between the estimations and actual observations. Potential clinical benefits were demonstrated with DCA. Additionally, for 1- and 2-year OS and 1-year PFS, patients were stratified into four groups with different survival probability by RPA.

Conclusion

The validated nomograms provided useful predictions of OS and PFS for LAPC with chemoradiotherapy.

Individualized Nomogram for Predicting Survival in Patients with Brain Metastases After Stereotactic Radiosurgery Utilizing Driver Gene Mutations and Volumetric Surrogates

It is well-known that genomic mutational analysis plays a significant role in patients with NSCLC for personalized treatment. Given the increasing use of stereotactic radiosurgery (SRS) for brain metastases (BM), there is an emerging need for more precise assessment of survival outcomes after SRS. Patients with BM and treated by SRS were eligible in this study. The primary endpoint was overall survival (OS). Cox regression models were used to identify independent prognostic factors. A survival predictive nomogram was developed and evaluated by Concordance-index (C-index), area under the curve (AUC), and calibration curve. From January 2016 to December 2019, a total of 356 BM patients were eligible. The median OS was 17.7 months [95% confidence interval (CI) 15.5–19.9] and the actual OS at 1- and 2-years measured 63.2 and 37.6%, respectively. A nomogram for OS was developed by incorporating four independent prognostic factors: Karnofsky Performance Score, cumulative tumor volume, gene mutation status, and serum lactate dehydrogenase. The nomogram was validated in a separate cohort and demonstrated good calibration and good discriminative ability (C-index = 0.780, AUC = 0.784). The prognostic accuracy of the nomogram (0.792) was considerably enhanced when compared with classical prognostic indices, including the Graded Prognostic Assessment (0.708), recursive partitioning analysis (0.587), and the SRS (0.536). Kaplan–Meier curves showed significant differences in OS among the stratified low-, median- and high-risk groups (P < 0.001). In conclusion, we developed and validated an individualized prognostic nomogram by integrating physiological, volumetric, clinical chemistry, and molecular biological surrogates. Although this nomogram should be validated by independent external study, it has a potential to facilitate more precise risk-stratifications to guide personalized treatment for BM.

Hypofractionated intensity-modulated radiotherapy with concurrent chemotherapy for elderly patients with locally advanced pancreatic carcinoma

BACKGROUND

It is important to understand how elderly patients with locally advanced pancreatic carcinoma (LAPC) should be treated, since the number of elderly cancer patients will increase. However, the optimal treatment for elderly patients with LAPC remains unclear. The purpose of this study was to evaluate the efficacy and safety of hypofractionated intensity-modulated radiotherapy (IMRT) with concurrent gemcitabine for elderly patients with LAPC.

METHODS

We retrospectively analysed the data from LAPC patients aged ≥ 75 years treated with hypofractionated IMRT (48 Gy in 15 fractions) with concurrent weekly gemcitabine at our institution from February 2013 to December 2018. Overall survival (OS), progression-free survival (PFS), locoregional progression-free survival (LRPFS), distant metastasis-free survival (DMFS), and the pattern of recurrence and toxicity were analysed.

RESULTS

Fifteen patients received treatment during the study period. The median age was 78 years (range 75-86 years), and the Eastern Cooperative Oncology Group (ECOG) performance status (PS) of all patients was 0-1. The median survival time (MST) and median PFS were 20.4 [95% confidence interval (CI) 10.3-36.8] and 13.5 (95% CI 6.4-20.3) months, respectively, and the 1-year OS and PFS rates were 80.0% (95% CI 50-93.1%) and 66.7% (95% CI 37.5-84.6%), respectively. The median LRPFS and median DMFS were 15.6 (95% CI 6.4-36.8) and 14.9 (95% CI 7.0-20.5) months, respectively, and the 1-year LRPFS and DMFS rates were 73.3% (95% CI 43.6-89.1%) and 66.7% (95% CI 37.5-84.6%), respectively. Non-haematologic grade 3 toxicity was observed in three cases, of which only one was induced by radiotherapy, whereas grade 4-5 non-haematologic acute or late toxicities were not observed.

CONCLUSIONS

The OS and PFS of elderly patients with LAPC treated using hypofractionated IMRT with concurrent gemcitabine were favourable and without the occurrence of severe toxicity. This treatment strategy is feasible and promising for elderly LAPC patients with good PS.

Equipping the American Joint Committee on Cancer Staging for Resectable Pancreatic Ductal Adenocarcinoma with Tumor Grade: A Novel Staging System

Background

The 8th American Joint Committee on Cancer (AJCC) staging system for pancreatic ductal adenocarcinoma (PDAC) outperforms its previous version in reproducibility but not in survival discrimination. Tumor grade, an indicator of the aggressive biology of PDAC, has been suggested as a reliable prognostic factor. This study aimed to construct a novel staging system with greater prognostication for resectable PDAC by incorporating tumor grade into the 8th AJCC system.

Methods

A total of 9966 patients with resectable PDAC from the Surveillance Epidemiology and End Results (SEER) database were randomly separated into training and interval validation sets. Another 324 patients from our center were included as an external validation set. We proposed a novel staging system by sorting the substages yielded by a combination of T, N, and tumor grade based on their overall survival (OS) and grouping them into several stages. Prognostic homogeneity and discrimination were determined using the likelihood ratio χ ² and the linear trend χ ² test, respectively. Prognostic accuracies were evaluated by the area under the receiver operating characteristics curve (AUC).

Results

Using the 8th AJCC system, the prognosis of patients within the same stage was quite heterogeneous among different substages. The multivariate Cox model identified the tumor grade (hazard ratio 1.333, 95% confidence interval 1.250-1.423, p < 0.001) was an independent prognostic factor of the OS. In the training set, the AUC, homogeneity, and discriminatory ability were superior for the novel staging system than for the 8th AJCC system (0.642 vs. 0.615, 403.4 vs. 248.6, and 335.1 vs. 218.0, respectively). Similar results were observed in the internal and external validation sets.

Conclusions

The novel staging system incorporating tumor grade into the 8th AJCC system was associated with better prognostic accuracy, homogeneity, and discriminatory ability among resectable PDAC patients. Moreover, the novel staging system also allowed possibly adjuvant chemotherapy decisions.

Radiomics Facilitates Candidate Selection for Irradiation Stents Among Patients With Unresectable Pancreatic Cancer

Purpose: To develop a model to select appropriate candidates for irradiation stent placement among patients with unresectable pancreatic cancer with malignant biliary obstruction (UPC-MBO). Methods: This retrospective study included 106 patients treated with an irradiation stent for UPC-MBO. These patients were randomly divided into a training group (74 patients) and a validation group (32 patients). A clinical model for predicting restenosis-free survival (RFS) was developed with clinical predictors selected by univariate and multivariate analyses. After integrating the radiomics signature, a combined model was constructed to predict RFS. The predictive performance was evaluated with the concordance index (C-index) in both the training and validation groups. The median risk score of progression in the training group was used to divide patients into high- and low-risk subgroups. Results: Radiomics features were integrated with clinical predictors to develop a combined model. The predictive performance was better in the combined model (C-index, 0.791 and 0.779 in the training and validation groups, respectively) than in the clinical model (C-index, 0.673 and 0.667 in the training and validation groups, respectively). According to the median risk score of 1.264, the RFS was significantly different between the high- and low-risk groups (p < 0.001 for the training group, and p = 0.016 for the validation group). Conclusions: The radiomics-based model had good performance for RFS prediction in patients with UPC-MBO who received an irradiation stent. Patients with slow progression should consider undergoing irradiation stent placement for a longer RFS.

Clinical usefulness of conversion surgery for unresectable pancreatic cancer diagnosed on multidetector computed tomography imaging: Results from a multicenter observational cohort study by the Hokkaido Pancreatic Cancer Study Group (HOPS UR-01)

BACKGROUND AND AIM

Effective multidisciplinary approaches for unresectable pancreatic cancer (UR-PC) that include modern chemotherapeutic regimens and subsequent conversion surgery (CS) are being developed. The aim of this study was to evaluate outcomes of patients clinically diagnosed with UR-PC, focusing on the efficacy of CS.

METHODS

Patients ineligible for two multicenter phase II studies conducted by the Hokkaido Pancreatic Cancer Study Group (HOPS) were recruited. Sequential treatment regimens, conversion to radical surgery, and overall survival (OS) were analyzed by multidetector computed tomography (MDCT)-based UR factors. Univariate and multivariate analyses were performed to identify predictors of OS.

RESULTS

Sixty-six of 247 intended recruits for HOPS studies from October 2013 to April 2016 were included. Unresectability was due to locally advanced (LA) disease and metastasis (M) in 42 and 24 patients, respectively. Induction therapy began with chemotherapy (CT) and chemoradiotherapy (CRT) in 44 and 17 patients, respectively, of whom 23 received modern CT regimens. Radical surgery was completed in 12 (LA, 10; M, two) with a median treatment interval of 10.3 months (range, 2-32). Eleven patients (91.6%) achieved pathological R0 resection. Median OS was significantly longer in patients who underwent CS than those who did not (44.1 vs 14.5 months, P < 0.0001). CS was an independent predictor of OS (hazard ratio, 0.078; 95% confident interval, 0.017-0.348; P = 0.001).

CONCLUSION

Conversion surgery after a favorable response to sequential treatment might prolong survival in patients with UR-PC. Precise diagnosis on MDCT followed by sequential multimodal anticancer treatment is essential.

Clinical characteristics and disease-specific prognostic nomogram for primary gliosarcoma: a SEER population-based analysis

Because the study population with gliosarcoma (GSM) is limited, the understanding of this disease is insufficient. In this study, the authors aimed to determine the clinical characteristics and independent prognostic factors influencing the prognosis of GSM patients and to develop a nomogram to predict the prognosis of GSM patients after craniotomy. A total of 498 patients diagnosed with primary GSM between 2004 and 2015 were extracted from the 18 Registries Research Data of the Surveillance, Epidemiology, and End Results (SEER) database. The median disease-specific survival (DSS) was 12.0 months, and the postoperative 0.5-, 1-, and 3-year DSS rates were 71.4%, 46.4% and 9.8%, respectively. We applied both the Cox proportional hazards model and the decision tree model to determine the prognostic factors of primary GSM. The Cox proportional hazards model demonstrated that age at presentation, tumour size, metastasis state and adjuvant chemotherapy (CT) were independent prognostic factors for DSS. The decision tree model suggested that age <71 years and adjuvant CT were associated with a better prognosis for GSM patients. The nomogram generated via the Cox proportional hazards model was developed by applying the rms package in R version 3.5.0. The C-index of internal validation for DSS prediction was 0.67 (95% confidence interval (CI), 0.63 to 0.70). The calibration curve at one year suggested that there was good consistency between the predicted DSS and the actual DSS probability. This study was the first to develop a disease-specific nomogram for predicting the prognosis of primary GSM patients after craniotomy, which can help clinicians immediately and accurately predict patient prognosis and conduct further treatment.