Prognostic Importance of Comorbidity and the Association Between Comorbidity and p16 in Oropharyngeal Squamous Cell Carcinoma

Survival trends and conditional survival in patients with pulmonary metastases from differentiated thyroid carcinoma

INTRODUCTION

Patients with pulmonary metastases from differentiated thyroid carcinoma (DTC) have a significantly poorer prognosis compared to DTC patients without metastases. This study aimed to establish a nomogram combined with dynamic survival analysis to predict the survival probability of patients with pulmonary metastases from differentiated thyroid carcinoma and compensate for the underestimation of survival in patients with very poor prognosis.

PATIENTS AND METHODS

Patient data were collected from the Surveillance, Epidemiological, and End Result (SEER) data resource from 2010 to 2019. Multivariate analysis was carried out by the Cox proportional hazards regression to construct a nomogram. Receiver operating characteristic (ROC) curves along with calibration were employed to assess the effectiveness of the model.The life table was used to estimate the conditional cancer-specific survival (CSS).

RESULTS

In the training set, the AUCs for the CSS nomogram were 0.728, 0.741, and 0.779, with a c-index of 0.682, indicating good predictive performance at 3, 5, and 10 years. In the validation set, the AUCs for the CSS nomogram were 0.706, 0.726, and 0.769, with a c-index of 0.696, while the AUCs for the 8th TNM staging system were 0.521, 0.555, and 0.601, with a c-index of 0.579. The overall 5-year conditional survival rate for patients increased slightly from 63.44 to 70.52%. The survival gap was greatest between patients aged <55 years and those aged ≥55 years.

CONCLUSION

We established a nomogram combined with dynamic survival analysis, which serve as promising options for prognosis estimation, to enhance personalized evaluation of survival risks and provide the basis for the development of more clinical treatment approaches.

Construction of a Tool to Predict Overall Survival of Patients With Primary Spinal Tumors After Surgical Resection: A Real-World Analysis Based on the Surveillance, Epidemiology, and End Results Database

BACKGROUND

We aim to construct a practical clinical prediction model to accurately evaluate the overall survival (OS) of patients with primary spinal tumors after primary tumor resection, thereby aiding clinical decision-making.

METHODS

A total of 695 patients diagnosed with a primary spinal tumor, selected from the Surveillance, Epidemiology, and End Results (SEER) database, were included in this study. The Cox regression algorithm was applied to the training cohort to build the prognostic nomogram model. The nomogram's performance in terms of discrimination, calibration, and clinical usefulness was also assessed in the internal SEER validation cohort. The fitted prognostic nomogram was then used to create a web-based calculator.

RESULTS

Four independent prognostic factors were identified to establish a nomogram model for patients with primary spinal tumors who had undergone surgical resection. The C-index (.757 for the training cohort and .681 for the validation cohort) and the area under the curve values over time (both >.68) showed that the model exhibited satisfactory discrimination in both the SEER cohort. The calibration curve revealed that the projected and actual survival rates are very similar. The decision curve analysis also revealed that the model is clinically valuable and capable of identifying high-risk patients.

CONCLUSIONS

After developing a nomogram and a web-based calculator, we were able to reliably forecast the postoperative OS of patients with primary spinal tumors. These tools are expected to play an important role in clinical practice, informing clinicians in making decisions about patient care after surgery.

Prognosis of radiotherapy in medullary thyroid carcinoma patients without distant metastasis

Background

Medullary thyroid carcinoma (MTC) is an advanced disease with a poor prognosis. Although radiotherapy is widely utilized to treat MTC, it is still controversial. MTC patients without distant metastases have not been investigated to explore indications for adjuvant radiotherapy. This study aims to investigate the impact of radiotherapy on the survival of MTC patients without distant metastases.

Methods

Data of MTC patients without distant metastasis who underwent total thyroidectomy between 2010 and 2015 were obtained from the Surveillance, Epidemiology and End Results (SEER) database. Propensity score matching was performed to analyze the relationship between radiotherapy and cancer-specific survival (CSS).

Results

Seventy-four of 718 MTC patients without distant metastases received radiotherapy and underwent total thyroidectomy. A total of 148 patients were screened via propensity score matching analysis. Multivariate Cox regression indicated that factors including age, sex, radiotherapy and chemotherapy were independent predictors of CSS. Based on these factors, MTC patients without distant metastasis were classified into two risk groups using a nomogram and risk classification system. The C-index of the nomogram was 0.791. The calibration curves showed good consistency of CSS between the actual observation and the nomogram prediction, and decision curve analysis (DCA) showed great clinical usefulness of the nomogram. The three-year CSS of the radiotherapy group was 85.3%, and that of the surgery group was 95%. Particularly, compared with the surgery group, the three-year CSS of subgroups of the radiotherapy group, including male patients and those aged >48 years, was decreased.

Conclusions

Radiotherapy results in worse CSS for MTC patients without distant metastases. To maximize benefits, decisions about individual radiotherapy should weigh its advantages and disadvantages.

A visualized dynamic prediction model for survival of patients with geriatric thyroid cancer: A population-based study

OBJECTIVE

Thyroid cancer (TC) is a common malignancy with a poor prognosis with aging. However, no accurate predictive survival model exists for patients with geriatric TC.We aimed to establish prediction models of prognosis in elderly TC.

METHODS

We retrospectively reviewed the clinicopathology characteristics of patients with geriatric TC in the Surveillance, Epidemiology, and End Results database (SEER) from 2004 to 2018. The risk predictors used to build the nomograms were derived from the Cox proportional risk regression. These nomograms were used to predict 1-, 3-, and 5-year overall survival and cancer-specific survival in elderly patients with TC. The accuracy and discriminability of the new model were evaluated by the consistency index (C-index) and calibration curve. The clinical applicability value of the model was assessed using the decision curve analysis.

RESULTS

We used the SEER database to include 16475 patients with geriatric TC diagnosed from 2004 to 2018. The patients from 2004 to 2015 were randomly sorted out on a scale of 7:3. They were classified into a training group (n = 8623) and a validation group (n = 3669). Patients with TC diagnosed in 2016-2018 were classified into external validation groups (n = 4183). The overall survival nomogram consisted of 10 variables (age, gender, marital status, histologic type, grade, TNM stage, surgery status, and tumor size). A cancer-specific survival nomogram consisted of eight factors (age, tumor size, grade, histologic type, surgery, and TNM stage). The C-index values for the training, validation, and external validation groups were 0.775 (95% confidence interval [CI] 0.785-0.765), 0.776 (95% CI 0.792-0.760), and 0.895(95% CI 0.873-0.917), respectively. The overall survival was consistent with a nomogram based on the calibration curve. Besides, the decision curve analysis showed excellent clinical application value of the nomogram. Additionally, we found that surgery could improve the prognosis of patients with geriatric at high-risk (P < 0.001) but not those at low-risk (P = 0.069).

CONCLUSION

This was the first study to construct predictive survival nomograms for patients with geriatric TC. The well-established nomograms and the actual results could guide follow-up management strategies.

[Smoking and co-morbidity - it's impact on dose achievement in radio(chemo)therapy for HNSCC]

Smoking worsens the prognosis of patients with HNSCC. Furthermore, smoking is associated with the prevalence of co- and multimorbidity, so that it is assumed that not smoking per se, but co-/multimorbidity worsens the prognosis due to lack of compliance to therapy, e. g. by reducing the dose of the planned radio(chemo)therapy (RCT). However, data on this topic are currently sparse and contradictory, especially for HNSCC.Patient records and tumor documentation of 643 consecutive cases of the Head and Neck Tumor Center of the University Hospital Kiel were retrospectively evaluated. Patient characteristics and smoking habits were recorded and correlated with co-/multimorbidity and treatment course.The 643 patient files examined show that 113 (17.6 %) patients did not smoke, 349 (54.3 %) were active and 180 (28 %) patients had previously smoked. 315 (49 %) are treated exclusively by surgery; 121 (18.8 %) by surgery + adjuvant RCT and 72 (11.2 %) by surgery + adjuvant RT. 111 (17.3 %) receive a primary RCT and 24 (3.7 %) a primary RT. 131 (20.4 %) show co-/multimorbidity and 512 (79.6 %) do not. Smoking (> 10 py) is significantly associated with comorbidity (p = 0.002). However, smoking and comorbidity, neither alone nor in combination, are correlated with the achievement of the target dose of RCT (p > 0.05).As expected, smoking is significantly linked to co-/multimorbidity. Dose reduction of R(C)T is just as frequent in active smokers and patients with co-/multimorbidity as in non-smokers and patients without co-/multimorbidity. Thus, smoking and co-/multimorbidity influence the prognosis in other ways than by interfering with planned therapy regimens.

Establishment and Verification of a Nomogram for Predicting Survival in Patients with Small Intestinal Gastrointestinal Stromal Tumors

BACKGROUND

This study aimed to develop and validate nomograms for predicting overall survival (OS) and cancer-specific survival (CSS) in small intestinal gastrointestinal stromal tumors (SI GISTs).

METHODS

Patients diagnosed with SI GISTs were retrieved from the Surveillance, Epidemiology, and End Results (SEER) database and further randomly divided into training and validating cohorts. Univariate and multivariate Cox analyses were conducted in the training set to determine independent prognostic factors to build nomograms for predicting 3- and 5-year OS and CSS. The performance of the nomograms was assessed by using the concordance index (C-index), calibration plot, and the area under the receiver operating characteristic curve (AUC).

RESULTS

Data of a total of 776 patients with SI GISTs were retrospectively collected from the SEER database. The OS nomogram was constructed based on age, surgery, imatinib treatment, and American Joint Committee for Cancer (AJCC) stage, while the CSS nomogram incorporated age, surgery, tumor grade, and AJCC stage. In the training set, the C-index for the OS nomogram was 0.773 (95% confidence interval [95% CI]: 0.722-0.824) and for the CSS nomogram 0.806 (95% CI: 0.757-0.855). In the internal validation cohort, the C-index for the OS nomogram was 0.741, while for the CSS nomogram, it was 0.819. Well-corresponded calibration plots both in OS and CSS nomogram models were noticed. The comparisons of AUC values showed that the established nomograms exhibited superior discrimination power than the 7th Tumor-Node-Metastasis staging system.

CONCLUSION

Our nomogram can effectively predict 3- and 5-year OS and CSS in patients with SI GISTs, and its use can help improve the accuracy of personalized survival prediction and facilitate to provide constructive therapeutic suggestions.

The association of smoking and outcomes in HPV-positive oropharyngeal cancer: A systematic review

PURPOSE

While smoking is linked to worse outcomes for human papillomavirus (HPV)-related oropharyngeal squamous cell cancer (OPSCC), the magnitude of this association and the amount of smoking exposure necessary to confer clinically significant differences in outcomes is unclear. Recent studies suggested that greater tobacco exposure results in higher risk of cancer progression and death. Our study objective was to perform a systematic review of the association between smoking and HPV-related OPSCC outcomes.

MATERIALS AND METHODS

A literature search was conducted in April 2019 to identify relevant articles using Embase, Medline, Scopus, CENTRAL, and Cochrane databases. All studies were independently screened by two investigators to identify studies that assessed HPV-positive patients as an independent cohort, specified smoking measures, and reported locoregional recurrence (LRR), overall survival (OS), disease-specific survival (DSS), or disease-free survival (DFS) in association with smoking.

RESULTS

Of 1130 studies identified, 10 met final inclusion criteria with 2321 total patients, mean age 57.5 years. Smoking measures included ever vs never, current vs never/former smokers, ≤10 vs >10 pack-year, and continuous pack-years. Of these studies, 8 (80%) showed a significant effect of smoking on increasing recurrence and mortality. Adjusted HRs for LRR ranged from 0.6 to 5.2, OS from 1.3 to 4.0, DSS from 2.3 to 7.2, and DFS from 1.02 to 4.2 among heavier smokers compared to lighter/non-smokers.

CONCLUSIONS

While there was significant variability in smoking metrics and reported outcomes, all studies reporting statistically significant HRs showed that smoking was associated with worse outcomes. Further studies using uniform smoking measures are necessary to better understand this association.

Development and validation of prognostic nomograms for pseudomyxoma peritonei patients after surgery: A population-based study

BACKGROUND

The aim of study was to develop and validate nomograms for predicting overall survival (OS) and cancer-specific survival (CSS) of patients with pseudomyxoma peritonei (PMP) and compare the predictive accuracy with the American Joint Committee on Cancer (AJCC) staging system.

METHODS

Data of 4959 PMP patients who underwent surgical resection were collected between 2004 and 2015 from the Surveillance Epidemiology and End Results (SEER) database. All included patients were divided into training (n = 3307) and validation (n = 1652) cohorts. The Kaplan-Meier method and Cox proportional hazard model were applied. Nomograms were validated by discrimination and calibration. Finally, concordance index (C-index) was used to compare the predictive performance of nomograms with that of the AJCC staging system.

RESULTS

According to the univariate and multivariate analyses of training sets, both nomograms for predicting OS and CSS combining age, grade, location, N stage, M stage, and chemotherapy were identified. Nomograms predicting OS also incorporated T stage and the number of lymph nodes removed (LNR). The calibration curves showed good consistency between predicted and actual observed survival. Moreover, C-index values demonstrated that the nomograms predicting both OS and CSS were superior to the AJCC staging system in both cohorts.

CONCLUSION

We successfully developed and validated prognostic nomograms for predicting OS and CSS in PMP patients. Two nomograms were more accurate and applicable than the AJCC staging system for predicting patient survival, which may help clinicians stratify patients into different risk groups, tailor individualized treatment, and accurately predict patient survival in PMP.

Prognostic factors in patients with gallbladder adenocarcinoma identified using competing-risks analysis: A study of cases in the SEER database

A competing-risks model was developed in this study to identify the significant prognostic factors and evaluate the cumulative incidence of cause-specific death in gallbladder adenocarcinoma (GBAC), with the aim of providing guidance on effective clinical treatments.All patients with GBAC in the Surveillance, Epidemiology, and End Results (SEER) database during 1973 to 2015 were identified. The potential prognostic factors were identified using competing-risks analyses implemented using the R and SAS statistical software packages. We calculated the cumulative incidence function (CIF) for cause-specific death and death from other causes at each time point. The Fine-Gray proportional-subdistribution-hazards model was then applied in univariate and multivariate analyses to test the differences in CIF between different groups and identify independent prognostic factors.This study included 3836 eligible patients who had been enrolled from 2004 to 2015 in the SEER database. The univariate analysis indicated that age, race, AJCC stage, RS, tumor size, SEER historic stage, grade, surgery, radiotherapy, chemotherapy and adjuvant therapy (RCT, SRT, SCT and SRCT) were significant factors affecting the probability of death due to GBAC. The multivariate analysis indicated that age, race, AJCC stage, RS status, tumor size, grade and SRT were independent prognostic factors affecting GBAC cancer-specific death. A nomogram model was constructed based on multivariate models for death related to GBAC.We have constructed the first competing-risks nomogram for GBAC. The model was found to perform well. This novel validated prognostic model may facilitate the choosing of beneficial treatment strategies and help when predicting survival.

Applying nomograms based on the surveillance, epidemiology and end results database to predict long-term overall survival and cancer-specific survival in patients with oropharyngeal squamous cell carcinomas: A case-control research

Few models regarding to the individualized prognosis assessment of oropharyngeal squamous cell carcinoma (OPSCC) patients were documented. The purpose of this study was to establish nomogram model to predict the long-term overall survival (OS) and cancer-specific survival (CSS) of OPSCC patients. The detailed clinical data for the 10,980 OPSCC patients were collected from the surveillance, epidemiology and end results (SEER) database. Furthermore, we applied a popular and reasonable random split-sample method to divide the total 10,980 patients into 2 groups, including 9881 (90%) patients in the modeling cohort and 1099 (10%) patients in the external validation cohort. Among the modeling cohort, 3084 (31.2%) patients were deceased at the last follow-up date. Of those patients, 2188 (22.1%) patients died due to OPSCC. In addition, 896 (9.1%) patients died due to other causes. The median follow-up period was 45 months (1-119 months). We developed 2 nomograms to predict 5- and 8- year OS and CSS using Cox Proportional Hazards model. The nomograms' accuracy was evaluated through the concordance index (C-index) and calibration curves by internal and external validation. The C-indexes of internal validation on the 5- and 8-year OS and CSS were 0.742 and 0.765, respectively. Moreover, the C-indexes of external validation were 0.740 and 0.759, accordingly. Based on a retrospective cohort from the SEER database, we succeeded in constructing 2 nomograms to predict long-term OS and CSS for OPSCC patients, which provides reference for surgeons to develop a treatment plan and individual prognostic evaluations.

Evaluation of lymph node ratio and lymph node yield as prognosticators of locoregional recurrence in p16-associated oropharyngeal squamous cell carcinoma

BACKGROUND

The prognostic value of lymph node yield (LNY) and lymph node ratio (LNR), or the ratio of number of metastatic LNs to total number dissected, has not been well established in p16-associated oropharyngeal squamous cell carcinoma (OPSCC).

METHODS

This retrospective cohort study evaluated locoregional disease-free survival (LRDFS) in 82 patients with p16+ OPSCC who underwent neck dissection at a single institution from 2009 to 2017. LNR and LNY cutoffs were estimated using time-dependent receiver operator characteristic (ROC) curves. Prognostic significance of these cutoffs was compared with Eighth Edition AJCC Nodal Staging.

RESULTS

An increased LNR ≥ 0.129 was associated with worse 2-year LRDFS (66.9% vs 96.8%, P = .005). LNY was not significantly associated with LRDFS (P = .304). An LNR-based risk model was a better prognosticator than Eighth Edition AJCC Nodal Staging (Harrell's C, 0.9065 vs 0.7668).

CONCLUSIONS

LNR has good prognostic utility in predicting LRDFS in p16+ OPSCC, but further evaluation of this measure is warranted.

A Nomogram and a Risk Classification System Predicting the Cancer-Specific Survival of Patients With Initially-Diagnosed Osseous Spinal and Pelvic Tumors

STUDY DESIGN

Retrospective analysis.

OBJECTIVE

Our goal was to provide a predictive model and a risk classification system that predicts cancer-specific survival (CSS) from spinal and pelvic tumors.

SUMMARY OF BACKGROUND DATA

Primary bone tumors of the spinal and pelvic are rare, thus limiting the understanding of the manifestations and survival from these tumors. Nomograms are the graphical representation of mathematical relationships or laws that accurately predict individual survival.

METHODS

A total of 1033 patients with spinal and pelvic bone tumors between 2004 and 2016 were selected from the Surveillance, Epidemiology, and End Results (SEER) database. Multivariate Cox analysis was used on the training set to select significant predictors to build a nomogram that predicted 3- and 5-year CSS. We validate the precision of the nomogram by discrimination and calibration, and the clinical value of nomogram was assessed by making use of a decision curve analyses (DCA).

RESULTS

Data from 1033 patients with initially-diagnosed spinal and pelvic tumors were extracted from the SEER database. Multivariate analysis of the training cohort, predictors included in the nomogram were age, pathological type, tumor stage, and surgery. The value of C-index was 0.711 and 0.743 for the internal and external validation sets, respectively, indicating good agreement with actual CSS. The internal and external calibration curves revealed good correlation of CSS between the actual observation and the nomogram. Then, the DCA showed greater net benefits than that of treat-all or treat-none at all time points. A novel risk grouping system was established for CSS that can readily divide all patients into three distinct risk groups.

CONCLUSION

The proposed nomogram obtained more precision prognostic prediction for patients with initially-diagnosed primary spinal and pelvic tumors.

LEVEL OF EVIDENCE

3.

Safety and Efficacy of Pembrolizumab With Chemoradiotherapy in Locally Advanced Head and Neck Squamous Cell Carcinoma: A Phase IB Study

PURPOSE

Pembrolizumab is a humanized monoclonal antibody that blocks interaction between programmed death receptor-1 (PD-1) and its ligands (PD-L1, PD-L2). Although pembrolizumab is approved for recurrent/metastatic head and neck squamous cell carcinoma (HNSCC), its role in the management of locally advanced (LA) disease is not defined. We report a phase IB study evaluating the safety and efficacy of adding pembrolizumab to cisplatin-based chemoradiotherapy in patients with LA HNSCC.

PATIENTS AND METHODS

Eligible patients included those with oral cavity (excluding lip), oropharyngeal, hypopharyngeal, or laryngeal stage III to IVB HNSCC (according to American Joint Committee on Cancer, 7th edition, staging system) eligible for cisplatin-based, standard-dose (70 Gy) chemoradiotherapy. Pembrolizumab was administered concurrently with and after chemoradiotherapy with weekly cisplatin. Safety was the primary end point and was determined by incidence of chemoradiotherapy adverse events (AEs) and immune-related AEs (irAEs). Efficacy was defined as complete response (CR) rate on end-of-treatment (EOT) imaging or with pathologic confirmation at 100 days postradiotherapy completion. Key secondary end points included overall (OS) and progression-free survival (PFS).

RESULTS

The study accrued 59 patients (human papillomavirus [HPV] positive, n = 34; HPV negative, n = 25) from November 2015 to October 2018. Five patients (8.8%) required discontinuation of pembrolizumab because of irAEs, all of which occurred during concurrent chemoradiotherapy; 98.3% of patients completed the full planned treatment dose (70 Gy) of radiotherapy without any delays ≥ 5 days; 88.1% of patients completed the goal cisplatin dose of ≥ 200 mg/m². EOT CR rates were 85.3% and 78.3% for those with HPV-positive and -negative HNSCC, respectively.

CONCLUSION

Pembrolizumab in combination with weekly cisplatin-based chemoradiotherapy is safe and does not impair delivery of curative radiotherapy or chemotherapy in HNSCC. Early efficacy data support further investigation of this approach.

A Nomogram for Predicting Cancer-Specific Survival of Patients with Gastrointestinal Stromal Tumors

Background

The aim of this study was to construct a nomogram to predict the prognosis of patients with gastrointestinal stromal tumor (GIST).

Material/Methods

We enrolled 4086 GIST patients listed in the SEER database from 1998 to 2015. They were separated to 2 groups: an experimental group (n=2862) and a verification group (n=1224). A nomogram was constructed by using statistically significant prognostic factors.

Result

A nomogram that included age, sex, marital status, tumor location, grade, SEER stage, tumor size, and surgical management was developed. It can be used to predict overall survival (OS), while adding AJCC 7^th TNM stage can predict cancer-specific survival (CSS). The C-index used to forecast OS and CSS nomograms was 0.778 (95% CI, 0.76–0.79) and 0.818 (95% CI, 0.80–0.84), respectively.

Conclusions

The nomogram can effectively predict 3- and 5-year CSS in patients with GIST, and its use can improve clinical practice.

Nomogram for predicting overall survival of patients with bladder cancer: A population-based study

OBJECTIVE

The aim of this study was to develop and validate a reliable nomogram to estimate overall survival in bladder cancer.

METHOD

Patients diagnosed with bladder cancer identified in the Surveillance, Epidemiology, and End Results database were randomly divided into training and validation cohorts. The powerful prognostic variables were examined using Cox regression analyses. A nomogram was developed on the prognostic factors.

RESULTS

The results suggested that age, sex, race, grade, histologic type, primary site, pathological stage, surgical treatment, and number of primary tumors, were the powerful prognostic factors. All these factors were integrated to construct the nomogram. The nomogram for predicting overall survival showed better discrimination power than the tumor-node-metastasis (TNM) stage system 8th edition.

CONCLUSION

The nomogram has the potential to provide an individualized prediction of overall survival in patients with bladder cancer.

Burden of comorbidities is higher among elderly survivors of oropharyngeal cancer compared with controls

BACKGROUND

The prevalence of survivors of oropharyngeal cancer (OPC) is increasing due to improved survival for individuals with human papillomavirus (HPV)-related disease. Although elderly survivors of OPC are known to have a high burden of comorbidities, to the authors' knowledge it is unknown how this compares with a similar cohort without a history of cancer.

METHODS

The current retrospective, cross-sectional study included individuals with a first incident primary diagnosis of OPC from 2004 through 2011 from the Surveillance, Epidemiology, and End Results (SEER)-Medicare-linked databases and matched controls. The baseline prevalence and subsequent incidence of comorbid conditions were identified. The association between comorbidity and overall survival was evaluated.

RESULTS

A total of 2497 eligible patients with OPC were matched to 4994 noncancer controls. Baseline comorbidity was higher in cases (Charlson Comorbidity Index >0 for 48.5% of cases vs 35.8% of controls). At 5 years, cases were more likely than controls to develop comorbidities. Survivors of OPC were at high risk (≥20% cumulative prevalence by 5 years) of developing several comorbidities, including cardiovascular diseases, cerebrovascular disease, chronic obstructive pulmonary disease, and tobacco abuse, and were at moderately high risk (10%-19% cumulative prevalence) of developing other conditions including carotid artery occlusive stroke, alcohol abuse, depression, and anxiety. In both cases and controls, the presence of the majority of comorbidities either at the time of diagnosis or during the follow-up period was associated with worse survival.

CONCLUSIONS

Patients with OPC have a higher comorbidity burden compared with matched controls, both at baseline and during survivorship, the majority of which are associated with decreased survival. Oncologic surveillance of survivors of OPC should include screening for highly prevalent conditions.

The Influence of Smoking and Co-morbidity on Dose Achievement in Primary or Adjuvant Radio(Chemo)Therapy in Head and Neck Squamous Cell Carcinoma (HNSCC)

Introduction: Smoking has a negative impact on survival of HNSCC patients. In addition, smoking is associated with the prevalence of co-morbidities and, thus, it may be assumed that not smoking per se but co-morbidities impact the course of therapy in terms of lower compliance and dose-reduction. However, data addressing this issue is sparse and conflicting at present, specifically for HNSCCs. Patients and methods: Patient files and tumor documentation from 643 consecutive cases of the University Head and Neck Cancer Centre Kiel were analyzed retrospectively. Patient characteristics and smoking habits were assessed and correlated with co-morbidities and course of treatment. Results: The examined 643 patient files showed that 113 (17.6%), 349 (54.3%), and 180 (28%) patients were never, active, and former smokers, respectively. Three hundred fifteen (49%) were treated by surgery only; 121 (18.8%) received surgery + adjuvant RCT and 72 (11.2%) surgery + adjuvant RT. 111 (17.3%) received primary RCT and 24 (3.7%) primary RT. 131 (20.4%) and 512 (79.6%) had no or had co-morbidities, respectively. Smoking (>10 py) was significantly associated with co-morbidities (p = 0.002). However, smoking and co-morbidities, neither alone nor in combination, were correlated with failure in reaching target doses of radio(chemo)therapy (p > 0.05). Applying (verified) Carlson-Comorbidity-Index (CCI) did not change the results. Conclusions: As expected, smoking is significantly associated with co-morbidities. Dose-reduction of radio(chemo)therapy is as common among active smokers and patients with co-morbidities as among never smokers and patients without co-morbidities. Thus, smoking and co-morbidity seems to impact survival by other means than impairing planned therapy regimens.

Oropharyngeal Squamous Cell Carcinoma in 390 Patients: Analysis of Clinical and Histological Criteria Which Significantly Impact Outcome

This study evaluates the prognostic impact of several factors in oropharyngeal squamous cell carcinoma (OPSCC), controlling for human papillomavirus (HPV)-associated tumors and stage (American Joint Committee on Cancer 8th edition). All patients in Southern California Permanente Medical Group diagnosed with OPSCC between 2006 and 2012 tested for p16 immunohistochemistry were included. Review of all pathology materials was combined with central p16 testing. Multivariable analyses were performed. The cohort of 390 patients included 342 p16-positive and 48 p16-negative tumors. For all-comers, on univariate analysis, the following factors, when present, were associated with improved patient survival: p16-positive tumor (n = 324, p < 0.001); crypt versus surface tumor location (n = 312, p = 0.004); nonkeratinizing type (n = 309, p < 0.0001); nonkeratinizing with maturation type (n = 37, p < 0.0001); basaloid pattern (n = 284, p = 0.005); and a broad, pushing border of infiltration (n = 282, p = 0.004). Inferior survival outcomes were observed with: age ≥ 55 years (p < 0.0001); ≥ 10 pack-year smoking history (n = 183, p = 0.003); increasing tumor stage (p < 0.0001); overt radiographic extranodal extension (ORENE) (n = 58, p < 0.0001); low level IV/Vb lymph node involvement (n = 45, p = 0.0002); a jagged pattern of infiltration (n = 76, p = 0.0004); tumor ulceration (n = 76, p = 0.0004); absent lymphocytic infiltrate (p < 0.0001); and concurrent dysplasia (n = 125, p = 0.009). On multivariable analysis, accounting for patient age, smoking history ≥ 10 pack-years, and TNM stage, for patients with p16-positive disease, advanced TNM stage (p = 0.007), the presence of ORENE (p = 0.0002), and low-neck lymphadenopathy (p = 0.0001) were independent negative prognostic factors for disease free survival (DFS). Older age (p < 0.0001), smoking history ≥ 10 pack-years (p = 0.02), advanced TNM stage (p = 0.0002), ORENE (p = 0.004), and low-neck lymphadenopathy (p = 0.002) were independent negative prognostic factors for OS. Among patients with p16-positive OPSCC, older age, smoking history, advanced stage, ORENE, and low-neck lymphadenopathy were significant negative prognostic factors for DFS and/or OS. Further refinement of staging to incorporate additional lymph node findings may be warranted.

Nomograms for predicting long-term overall survival and cancer-specific survival in lip squamous cell carcinoma: A population-based study

Background

The goal of this study was to establish and validate two nomograms for predicting the long‐term overall survival (OS) and cancer‐specific survival (CSS) in lip squamous cell carcinoma (LSCC).

Methods

This study selected 4175 patients who were diagnosed with LSCC between 2004 and 2015 in the SEER (Surveillance, Epidemiology, and End Results) database. The patients were allocated randomly to a training cohort and validation cohort. Variables were selected using a backward stepwise method in a Cox regression model. Based on the predictive model with the identified prognostic factors, nomograms were established to predict the 3‐, 5‐, and 8‐year survival OS and CSS rates of LSCC patients. The accuracy of the nomograms was evaluated based on the consistency index (C‐index), while their prediction accuracy was evaluated using calibration plots. Decision curve analyses (DCAs) were used to evaluate the performance of our survival model.

Results

The multivariate analyses demonstrated that age at diagnosis, marital status, sex, race, American Joint Committee on Cancer stage, surgery status, and radiotherapy status were risk factors for both OS and CSS. The C‐index, area under the time‐dependent receiver operating characteristic curve, and calibration plots demonstrated the good performance of the nomograms. DCAs of both nomograms further showed that they exhibited good 3‐, 5‐, and 8‐year net benefits.

Conclusions

We have developed and validated LSCC prognosis nomograms for OS and CSS for the first time. These nomograms can be valuable tools for clinical practice when clinicians are helping patients to understand their survival risk for the next 3, 5, and 8 years.

Development and validation of prognostic nomograms for medullary thyroid cancer

Background

This aim of study was to develop and validate clinical nomograms to predict the survival of patients with medullary thyroid cancer.

Patients and methods

Patient data were collected from the Surveillance, Epidemiology, and End Results database between 2004 and 2013. All included patients were randomly assigned into the training and validation sets. Multivariate analysis using Cox proportional hazards regression was performed, and nomograms were constructed. Model performance was evaluated by discrimination and calibration plots.

Results

A total of 1,657 patients were retrospectively analyzed. The multivariate Cox model identified age, tumor size, extrathyroidal extension, N stage, and M stage as independent covariates associated with overall survival (OS) and cancer-specific survival (CSS). Nomograms predicting OS and CSS were constructed based on these covariates. The nomograms predicting both OS and CSS exhibited superior discrimination power to that of TNM staging system in the training and validation sets. Calibration plots indicated that both the nomograms in OS and CSS exhibited high correlation to actual observed results.

Conclusion

The nomograms established in this study provided an alternative tool for prognostic prediction, which may thereby improve individualized assessment of survival risks and lead to the creation of additional clinical therapies.

Association between comorbidity and survival in head and neck cancer: Results from Head and Neck 5000

BACKGROUND

People with head and neck cancer have higher comorbidity levels but it remains unclear if pretreatment comorbidity is an independent prognosticator in head and neck cancer.

METHODS

Survival analyses were performed using data from participants in a UK multicentre cohort study with cancers of the oral cavity (n = 668), oropharynx (n = 1074), and larynx (n = 530). Survival analyses were incrementally adjusted for age, sex, marital status, income, education, stage, alcohol, and smoking.

RESULTS

After adjusting for demographic, clinical, and behavioral confounders, higher baseline comorbidity was associated with reduced overall survival (mild comorbidity HR = 1.4, 95% CI = 1.1, 1.7; moderate comorbidity HR = 1.7, 95% CI = 1.3, 2.2; severe comorbidity HR = 2.8, 95% CI = 1.9, 4.; P-trend<.001).

CONCLUSIONS

Our findings suggest that comorbidity is an independent prognosticator for overall survival in head and neck cancer. Comorbid illnesses should be considered in the assessment and treatment planning of people with head and neck cancer.

Nomograms for estimating survival in patients with liver-only colorectal metastases: A retrospective study

BACKGROUND

The aim of this study was to develop and validate nomograms for individual risk prediction in patients with liver-only colorectal metastases (CRLM).

METHODS

Histologically confirmed CRLM diagnosed between 2010 and 2015 were analysed from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate analyses were used to obtain independent prognostic factors to build nomograms for predicting 1- and 3-year overall survival (OS) and cancer-specific survival (CSS). The predictive accuracy of the nomogram was determined by concordance index (C-index) and calibration plots.

RESULTS

A total of 9615 patients with CRLM were included in the study. A nomogram predicting OS was constructed according to 9 independent clinicopathological factors. A nomogram predicting CSS was constructed based on the same 9 factors. The C-indexes of the nomograms were significantly better than the TNM staging system (7th edition) in both sets for predicting both OS and CSS. The calibration plots displayed an optimal agreement between the predictive results and the actual observed outcomes.

CONCLUSIONS

The proposed nomograms can help clinicians calculate the probability in patients with CRLM.

Development and validation of a nomogram for predicting survival in patients with gastrointestinal stromal tumours

BACKGROUND

This study aimed to develop and validate nomograms for predicting long-term overall survival (OS) and cancer-specific survival (CSS) in gastrointestinal stromal tumours (GISTs).

METHODS

Patients diagnosed with GISTs between 2004 and 2015 were selected for the study from the Surveillance, Epidemiology, and End Results (SEER) database. Patients were randomly separated into the training set and the validation set. Multivariate analysis was used on the training set to obtain independent prognostic factors to build nomograms for predicting 3- and 5-year OS and CSS. The discrimination and calibration plots were used to evaluate the predictive accuracy of the nomograms.

RESULTS

Data for a total of 5622 patients with GISTs were collected from the SEER database. Nomograms were established based on variables that were significantly associated with OS and CSS identified by the Cox regression model. The nomograms for predicting OS and CSS displayed better discrimination power than did the SEER stage and Tumour-Node-Metastasis (TNM) staging systems (7th edition) in the training set and validation set. Calibration plots of the nomograms indicated that OS and CSS closely corresponded to actual observation.

CONCLUSIONS

The nomograms were able to more accurately predict 3- and 5-year OS and CSS of patients with GISTs than were existing models.

Development and Validation of a Nomogram for Predicting Overall Survival in Pancreatic NeuroendocrineTumors

BACKGROUND: The objective of current study was to develop and validate a nomogram to predict overall survival in pancreatic neuroendocrine tumors (PNETs). METHODS: The Surveillance, Epidemiology, and End Results (SEER) database was queried for patients with PNETs between 2004 and 2015. Patients were randomly separated into the training set and the validation set. Cox regression model was used in training set to obtain independent prognostic factors to develop a nomogram for predicting overall survival (OS). The discrimination and calibration plots were used to evaluate the predictive accuracy of the nomogram. RESULTS: A total of 3142 patients with PNETs were collected from the SEER database. Sex, age, marital status, primary site, TNM stage, tumor grade, and therapy were associated with OS in the multivariate models. A nomogram was constructed based on these variables. The nomogram for predicting OS displayed better discrimination power than the Tumor-Node-Metastasis (TNM) stage systems 7th edition in the training set and validation set. The calibration curve indicated that the nomogram was able to accurately predict 3- and 5-year OS. CONCLUSIONS: The nomogram which could predict 3- and 5-year OS were established in this study. Our nomogram showed a good performance, suggesting that it could be served as an effective tool for prognostic evaluation of patients with PNETs.

A nomogram to predict overall survival for biliary tract cancer

Background

The aim of the study was to develop and validate a nomogram to predict overall survival (OS) in biliary tract cancer (BTC).

Patients and methods

Patients diagnosed with BTC between 2004 and 2014 were selected for the study from the Surveillance, Epidemiology, and End Results (SEER) database. All patients were randomly allocated to 2 sets, the training set (n = 8,869) and the validation set (n = 8,766), for the purposes of validation. The prognostic effects of each variable were examined using univariate and multivariate analyses. Cox regression models and a nomogram were developed based on significant prognostic factors. The predictive and discriminatory capacity of the nomogram was evaluated by Harrell’s concordance index (C-index) and calibration plots.

Results

Data of 17,635 patients with BTC were collected from the SEER database. Age; race; tumor site; tumor grade; T, N, and M stage; marital status; and therapy were associated with survival in the multivariate models. All these factors were integrated to construct the nomogram. The nomogram for predicting OS displayed better discrimination power than the tumor-node-metastasis (TNM) stage system 6th edition in the training set and validation set. The calibration curve indicated that the nomogram was able to accurately predict 3- and 5-year OS.

Conclusion

This predictive model has the potential to provide an individualized risk estimate of survival in patients with BTC.

Nomograms predicting long-term overall survival and cancer-specific survival in head and neck squamous cell carcinoma patients

This study aimed to develop nomograms to predict long-term overall survival and cancer-specific survival in patients with head and neck squamous cell carcinoma (HNSCC). We conducted prognostic analyses and developed nomograms predicting survival outcome using HNSCC patient data collected from the Surveillance, Epidemiology and End Results (SEER) program of the National Cancer Institute. An external dataset of 219 patients was used to validate the nomograms. Of 36,179 HNSCC patients, 9,627 (26.6%) died from HNSCC and 4,229 (11.7%) died from other causes. Median follow-up was 28 months (1-107 months). Nomograms predicting overall survival (OS) and cancer-specific survival (CSS) were developed according to 10 clinicopathologic factors (age, race, sex, tumor site, tumor grade, surgery, radiotherapy and TNM stage), with concordance indexes (C-indexes) of 0.719 and 0.741, respectively. External validation C-indexes were 0.709 and 0.706 for OS and CSS, respectively. Our results suggest that we successfully developed nomograms predicting five- and eight-year HNSCC patient OS and CSS with high accuracy. These nomograms could help clinicians tailor surgical, adjuvant therapeutic and follow-up strategies to more effectively treat HNSCC patients.

Nomogram for predicting survival in patients with pancreatic cancer

Background

The purpose of this study was to develop a nomogram to predict cancer-specific survival (CSS) in pancreatic cancer (PC).

Patients and methods

We used the Surveillance, Epidemiology, and End Results (SEER) database to analyze 53,028 patients diagnosed with PC from 2004 to 2014 and randomly divided them into the training (n=26,583) cohort and validation (n=26,445) cohort. Univariate and multivariate analyses were used to select independent prognostic factors. We used significant prognostic factors for constructing a nomogram based on Cox regression analyses. Validation of the nomogram was assessed by discrimination and calibration.

Results

According to the multivariate models of training cohort, a nomogram that combined age, race, tumor location, marital status, tumor size, TNM stage, tumor grade, and surgery was constructed for predicting CSS. The internally validated and externally validated C-indexes were 0.741 and 0.734, respectively. The calibration curves showed that the nomogram was able to predict 1-, 3-, and 5-year CSS accurately.

Conclusion

A nomogram effectively predicts survival in patients with PC. This prognostic model may be considered for use in clinical practice.