scholarly journals Development and Validation of Nomograms to Predict Prognosis of Oral and Oropharyngeal Mucoepidermoid Carcinoma: A SEER-Based Study

2020 ◽  
Author(s):  
muyuan liu ◽  
Litian Tong ◽  
Manbin Xu ◽  
Xiang Xu ◽  
Bin Liang ◽  
...  
Keyword(s):  
Overall Survival ◽  
Prognostic Factors ◽  
Mucoepidermoid Carcinoma ◽  
Cox Regression ◽  
Seer Database ◽  
Disease Specific Survival ◽  
Cox Regression Analysis ◽  
T Stage ◽  
N Stage ◽  
Disease Specific

Abstract Background: Due to the low incidence of mucoepidermoid carcinoma, there lacks sufficient studies for determining optimal treatment and predicting prognosis. The purpose of this study was to develop prognostic nomograms, to predict overall survival and disease-specific survival (DSS) of oral and oropharyngeal mucoepidermoid carcinoma patients, using the National Cancer Institute’s Surveillance, Epidemiology, and End Results (SEER) database. Methods: Clinicopathological and follow-up data of patients diagnosed with oral and oropharyngeal mucoepidermoid carcinoma between 2004 and 2017 were collected from the SEER database. The Kaplan-Meier method with the log-rank test was employed to identify single prognostic factors. Multivariate Cox regression was utilized to identify independent prognostic factors. C-index, area under the ROC curve (AUC) and calibration curves were used to assess performance of the prognostic nomograms. Results: A total of 1230 patients with oral and oropharyngeal mucoepidermoid carcinoma were enrolled in the present study. After multivariate Cox regression analysis, age, sex, tumor subsite, T stage, N stage, M stage, grade and surgery were identified as independent prognostic factors for overall survival. T stage, N stage, M stage, grade and surgery were identified as independent prognostic factors for disease-specific survival. Nomograms were constructed to predict the overall survival and disease-specific survival based on the independent prognostic factors. The fitted nomograms possessed excellent prediction accuracy, with a C-index of 0.899 for OS prediction and 0.893 for DSS prediction. Internal validation by computing the bootstrap calibration plots, using the validation set, indicated excellent performance by the nomograms. Conclusion: The prognostic nomograms developed, based on individual clinicopathological characteristics, in the present study, accurately predicted the overall survival and disease-specific survival of patients with oral and oropharyngeal mucoepidermoid carcinoma.

Prognostic Factors Influencing Survival in Solitary Plasmacytoma: A SEER Database Analysis.

Blood ◽  
2008 ◽  
Vol 112 (11) ◽  
pp. 1670-1670
Author(s):  
Paul Mehan ◽  
Giridharan Ramsingh ◽  
Jingqin Luo ◽  
Daniel Morgansztern ◽  
Ravi Vij
Keyword(s):  
Multiple Myeloma ◽  
Overall Survival ◽  
Multivariate Analysis ◽  
Prognostic Factors ◽  
Solitary Plasmacytoma ◽  
Seer Database ◽  
Disease Specific Survival ◽  
Factors Influencing ◽  
Younger Age ◽  
Disease Specific

Abstract Solitary plasmacytoma (PCM) is a focal, neoplastic, plasma cell disorder without evidence of systemic disease. While PCM is a clinically distinct entity, survival can be limited by progression to multiple myeloma. Prior studies have attempted to identify factors influencing survival in PCM but have been limited by small patient cohorts. This study identified 1472 patients with PCM using the SEER database between 1988 and 2004. The median age of the patients was 64 years (range 12–97), 65.4% male, 34.6% female, 83% Caucasians, 10.7% African Americans and 6.3% other races. 63.8% had medullary PCM and 36.2% extramedullary PCM. 84% of medullary PCM occurred in axial skeleton and the rest in appendicular skeleton. Extramedullary PCM most frequently occurred in the head and neck region (51.4%) followed by skin/subcutaneous tissue (16.2%), GI tract 6% and other sites (26.4%). 55.2% were treated with radiation therapy alone, 29.5% with radiation therapy and surgery and 15.3% with surgery alone. 558 died during this period and the mean overall survival was 6.83 years (range, 0–16.9). The cause of death was multiple myeloma in 49.6%, other cancers 20.9% and cardiovascular diseases 12.9%. In all patients, survival probability at one year was 87.6% (95% CI, 85–89%), at five years was 58.9% (95% CI, 56–62%), and at 10 years was 40.0% (95% CI, 36–44%). The five year overall survival in the ≤40yo cohort was 83.5% as compared to 76.7% and 44.8% in the 40–60yo and >60yo groups, respectively (p<0.0001). The five year disease specific survival probability in the ≤40yo cohort was 94.5% as compared to 86.0% and 66.2% in the 40–60yo group and >60yo group, respectively (p<0.0001) (figure 1)). Overall survival in the extramedullary PCM was 65.9% at five years as compared to 54.6% in the medullary PCM (p<0.0001) and the disease specific survival in the extramedullary PCM was 86.2% compared to 70.1% in the medullary PCM (p<0.0001) (figure 1). Multivariate analysis of disease specific survival revealed that younger age, male gender, extramedullary type, and race other than African American or Caucasian were favorable prognostic factors (Table 1). Younger age, extramedullary site, treatment with XRT + surgery, and race other than African Americans were associated with improved overall survival by multivariate analysis (Table 1). To our knowledge, this is the largest published review of survival in PCM. This study identifies several prognostic risk factors influencing survival in PCM. These risk factors can be used to identify patients at high risk for progression to multiple myeloma. Those at highest risk could be considered for future trials comparing adjuvant systemic therapy compared to local therapy alone. Table 1. Multivariate Analysis of Prognostic Factors Disease Specific Survival Overall Survival Variable Category HR 95% CI P HR 95%CI P Abbreviations: HR, Hazard Ratio; Q, Confidence Inverval Sex Female --- -- --- -- --- --- Male 0.74 0.58~ 0.94 0.01 0.95 0.80~1.13 0.57 Age <40yo --- --- --- --- --- --- 40–60yo 2.68 115~ 6.2 0.02 1.74 1.04~2.91 0.03 >60yo 6.94 3.06~ 15.73 <0.01 5.55 3.40~9.06 <0.01 Race Black --- --- --- --- --- --- White 0.74 0.52~ 1.06 0.1 0.72 0.56~0.92 0.01 Others 0.31 0.13~ 0.75 <0.01 0.48 0.29~0.79 <0.01 Primary Site Extramedullary --- --- --- --- --- --- Medullary 2.35 1.74~.3.18 <0.01 1.37 1.13~1.65 <0.01 Treatment Surgery Only --- --- --- --- --- --- XRT Only 0.90 0.62~ 1.31 0.59 0.82 0.64~1.04 0.10 XRT + Surgery 0.84 0.55~1.26 0.39 0.68 0.52~0.89 <0.01 Period 1988–1993 --- --- --- --- --- --- 1994–1999 0.96 0.72~1.30 0.8 0.96 0.78~1.19 0.74 2000–2004 0.94 0.68~1.30 0.7 0.94 0.75~1.18 0.6 Figure 1: Figure 1:.

scholarly journals A nomogram predicting overall survival in patients with non-metastatic pancreatic head adenocarcinoma after surgery: a population-based study

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Wenbo Zou ◽  
Zizheng Wang ◽  
Fei Wang ◽  
Gong Zhang ◽  
Rong Liu
Keyword(s):  
Overall Survival ◽  
Prognostic Factors ◽  
Cox Regression ◽  
Predictive Accuracy ◽  
Pancreatic Head ◽  
Staging System ◽  
Seer Database ◽  
Cox Regression Analysis ◽  
Net Reclassification Improvement ◽  
Calibration Curves

Abstract Background Pancreatic head adenocarcinoma (PHAC), a malignant tumour, has a very poor prognosis, and the existing prognostic tools lack good predictive power. This study aimed to develop a better nomogram to predict overall survival after resection of non-metastatic PHAC. Methods Patients with non-metastatic PHAC were collected from the Surveillance, Epidemiology, and End Results (SEER) database and divided randomly into training and validation cohorts at a ratio of 7:3. Cox regression analysis was used to screen prognostic factors and construct the nomogram. Net reclassification improvement (NRI) and integrated discrimination improvement (IDI) were calculated to evaluate the performance of the model. The predictive accuracy and clinical benefits of the nomogram were validated using the area under the curve (AUC), calibration curves, and decision curve analysis (DCA). Results From 2010 to 2016, 6419 patients with non-metastatic PHAC who underwent surgery were collected from the SEER database. A model including T stage, N stage, grade, radiotherapy, and chemotherapy was constructed. The concordance index of the nomogram was 0.676, and the AUCs of the model assessing survival at multiple timepoints within 60 months were significantly higher than those of the American Joint Committee on Cancer (AJCC) 8th staging system in the training cohort. Calibration curves showed that the nomogram had ability to predict the actual survival. The NRI, IDI, and DCA curves also indicated that our nomogram had higher predictive capability and clinical utility than the AJCC staging system. Conclusions Our nomogram has an ability to predict overall survival after resection of non-metastatic PHAC and includes prognostic factors that are easy to obtain in clinical practice. It would help assist clinicians to conduct personalized medicine.

scholarly journals Incidence, Survival, and Associated Factors Estimation in Osteosarcoma Patients with Lung Metastasis: A Single-center Experience of 11 Years in Tianjin, China

2021 ◽  
Author(s):  
Chao Zhang ◽  
Haixiao Wu ◽  
Guijun Xu ◽  
Wenjuan Ma ◽  
Lisha Qi ◽  
...  
Keyword(s):  
Risk Factors ◽  
Overall Survival ◽  
Regression Analysis ◽  
Prognostic Factors ◽  
Lung Metastasis ◽  
Associated Factors ◽  
Cox Regression ◽  
Cancer Center ◽  
Single Center ◽  
Cox Regression Analysis

Abstract Background: Osteosarcoma is the most common primary malignant bone tumor. The current study was conducted to describe the general condition of patients with primary osteosarcoma in a single cancer center in Tianjin, China and to investigate the associated factors in osteosarcoma patients with lung metastasis. Methods: From February 2009 to October 2020, patients from Tianjin Medical University Cancer Institute and Hospital, China were retrospectively analyzed. The Kaplan–Meier method was used to evaluate the overall survival of osteosarcoma patients. Prognostic factors of patients with osteosarcoma were identified by the Cox proportional hazard regression analysis. Risk factor of lung metastasis in osteosarcoma were investigated by the logistic regression model. Results: A total of 203 patients were involved and 150 patients were successfully followed up for survival status. The 5-year survival rate of osteo-sarcoma patients was 70.0%. Surgery, bone and lung metastasis were the significant prognostic factors in multivariable Cox regression analysis. Twenty-one (10.3%) patients showed lung metastasis at the diagnosis of osteosarcoma and 67 (33%) lung metastases during the later course. T3 stage (OR=11.415, 95%CI 1.362-95.677, P=0.025) and synchronous bone metastasis (OR=6.437, 95%CI 1.69-24.51, P=0.006) were risk factors of synchronous lung metastasis occurrence. Good necrosis (≥90%, OR=0.097, 95%CI 0.028-0.332, P=0.000) and elevated Ki-67 (≥50%, OR=4.529, 95%CI 1.241-16.524, P=0.022) were proved to be significantly associated with metachronous lung metastasis occurrence. Conclusion: The overall survival, prognostic factors and risk factors for lung metastasis in this single center provided insight about osteosarcoma management.

Overall Survival Rate Analysis For Risk Factors In Women With Neuroendocrine Carcinoma of The Cervix Using Surveillance, Epidemiology, And End Results (SEER) Database

2021 ◽  
Author(s):  
Ziran Yin ◽  
Xiumin Huang
Keyword(s):  
Overall Survival ◽  
Lymph Nodes ◽  
Neuroendocrine Carcinoma ◽  
Cox Regression ◽  
Analysis Data ◽  
Seer Database ◽  
Regional Lymph Nodes ◽  
Data Set ◽  
Cox Models ◽  
Cox Regression Analysis

Abstract Background: Neuroendocrine carcinoma of the cervix is rare and aggressive disease, of which prognosis information and the effectiveness of the therapies is unclear.Methods: A retrospective study using data from the SEER database for the first diagnosed Neuroendocrine carcinoma of the cervix patients was conducted. We performed univariate and multivariate Cox models to screen for independent prognostic factors for overall survival. Subgroup analysis and sensitive analysis were performed for further study, then again univariate and multivariate analyses of Cox regression analysis were performed based on the sensitivity analysis data set.Results: A total of 250 Neuroendocrine carcinoma of the cervix cases was included, tumor subtype, age, marriage, race, number of regional lymph nodes, number of positive lymph nodes, radiotherapy, surgery, and FIGO stage were all factors affecting OS, and multivariate analysis identified FIGO staging (HR, 2.4; 95% CI, 1.505-3.828, P < 0.001) and surgery (HR, 0.467; 95% CI, 0.358-0.609, P < 0.001) treatment as independent indicators. With respect to the factors associated with treatments, we found that patients who underwent surgery (yes vs. no vs. unknown) or radiation (yes vs. no) experienced prolonged survival, both P < 0.001Conclusions: Our investigation shows that for patients with NECC surgery seems to be the effective treatment. Chemotherapy cannot improve the prognosis of NECC patients, and the effectiveness of radiation should be further verified.

scholarly journals Conditional Survival After Surgical Resection of Appendiceal Tumors: a Population-based Study

2021 ◽  
Author(s):  
Shutao Zhao ◽  
Chang Lu ◽  
Junan Li ◽  
Chao Zhang ◽  
Xudong Wang
Keyword(s):  
Prognostic Factors ◽  
Cox Regression ◽  
Population Based ◽  
Conditional Survival ◽  
Seer Database ◽  
Cancer Specific Survival ◽  
Population Based Study ◽  
Factors Affecting ◽  
Probability Of Survival ◽  
N Stage

Abstract Background: This study aimed to evaluate the conditional survival (CS) of appendiceal tumors (ATs) after surgery.Methods: A total of 3,031 patients with ATs who underwent surgery were included in the Surveillance Epidemiology and End Results (SEER) database from 2004 to 2016. A multivariate Cox regression model was used to analyze the prognostic factors affecting overall survival (OS) and cancer-specific survival (CSS). CS was used to calculate the probability of survival for another 3 years after the patient had survived x years. The formulas were COS3 = OS (x + 3) /OS (x), and CCS3 = CSS (x + 3)/CSS (x).Results: The 1-year, 3-year, and 5-year OSs for all patients were 95.6%, 83.3%, and 73.9%, respectively, while the 1-year, 3-year, and 5-year CSSs were 97.0%, 87.1%, and 79.9%, respectively. Age, grade, histology, N stage, carcinoembryonic antigen (CEA), and radiation were independent prognostic factors for OS and CSS. For patients that survived for 1 year, 3 years, and 5 years, their COS3s were 81.7%, 83.9%, and 87.0%, respectively. The CCS3s were 85.5%, 88.3%, and 92.0% respectively. In patients with poor clinicopathological factors, COS3 and CCS3 increased significantly, and the survival gap between OS and COS3, CSS and CCS3 was more obvious.Conclusions: CS for appendiceal tumors were dynamic and increased over time, especially in patients with poor prognosis.

scholarly journals Construction of a nomogram to predict overall survival for patients with lung large cell neuroendocrine carcinoma: analysis of the SEER database

2020 ◽  
Author(s):  
Dong Han ◽  
Fei Gao ◽  
Nan Li ◽  
Hao Wang ◽  
Qi Fu
Keyword(s):  
Overall Survival ◽  
Survival Rate ◽  
Neuroendocrine Carcinoma ◽  
Cox Regression ◽  
Risk Group ◽  
Multivariable Analysis ◽  
Large Cell ◽  
Large Cell Neuroendocrine Carcinoma ◽  
Seer Database ◽  
Cox Regression Analysis

Abstract Background Lung large cell neuroendocrine carcinoma (L-LCNEC) has a poor prognosis with lower survival rate than other NSCLC patients. The estimation of an individual survival rate is puzzling. The main purpose of this study was to establish a more accurate model to predict the prognosis of L-LCNEC.Methods Patients aged 18 years or older with L-LCNEC were identified from the Surveillance, Epidemiology and End Results (SEER) database from 2004 to 2015. Cox regression analysis was used to identify factors associated with survival time. The results were used to construct a nomogram to predict 1-year, and 3-year survival probability in L-LCNEC patients. Overall survival (OS) were compared between low risk group and high risk group by the Kaplan–Meier analysis.Results A total of 3216 patients were included in the study. We randomly divided all included patients into 7:3 training and validating groups. In multivariable analysis of training cohort, age at diagnosis, sex, stage of tumor, surgical treatment, radiotherapy and chemotherapy were independent prognostic factors for OS. All these factors were incorporated to construct a nomogram, which was tested in the validating cohort.Conclusions we constructed a visual nomogram prognosis model, which had the potential to predict the 1-year and 3-year survival rate of L-LCNEC patients, and could be used as an assistant prediction tool in clinical practice.

Prognostic value of risk stratification using blood biochemical parameters in Japanese patients with metastatic renal cell carcinoma treated by nivolumab.

2020 ◽  
Vol 38 (6_suppl) ◽  
pp. 724-724
Author(s):  
Yoshiaki Yamamoto ◽  
Hideyasu Matsuyama ◽  
Hiroaki Matsumoto ◽  
Shigeru Sakano ◽  
Nakanori Fujii ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Overall Survival ◽  
Prognostic Factors ◽  
Prognostic Value ◽  
Japanese Patients ◽  
Prognostic Scores ◽  
Disease Specific Survival ◽  
Previously Treated ◽  
Disease Specific ◽  
Metastatic Rcc

724 Background: Nivolumab is a standard treatment for previously treated advanced renal-cell carcinoma (RCC). However, nivolumab is effective in only a limited number of patients; therefore, we evaluated the prognostic value of several biomarkers, including inflammation-based prognostic scores and changes in these scores following nivolumab treatment in Japanese patients with metastatic RCC. Methods: We retrospectively reviewed the medical records of 65 patients with previously treated metastatic RCC and who received nivolumab. MSKCC and IMDC risk, inflammation-based prognostic scores, including neutrophil/lymphocyte ratio (NLR), platelet/lymphocyte ratio (PLR), lymphocyte/monocyte ratio (LMR), and Glasgow prognostic score before and 6 weeks after the treatment were recorded. Categorical variables influencing disease-specific and overall survival were compared using Cox proportional-hazards regression models. Results: Univariate analysis showed that MSKCC risk score ( P = 0.0052), lactate dehydrogenase (LDH) ( P = 0.0266), LMR ( P = 0.0113), and PLR ( P = 0.0017) had a significant effect on disease-specific survival. Multivariate analyses showed that PLR and LDH were found to be independent prognostic factors for disease-specific survival ( P = 0.0008, RR = 7.95, 95% CI, 2.16–51.64 and P = 0.0123, RR = 3.92, 95% CI, 1.37–10.80, respectively). The combination of PLR and LDH was the most significant prognostic biomarker in metastatic RCC for disease-specific ( P < 0.0001) and overall ( P < 0.0001) survival. Changes in LMR and PLR in response to nivolumab were significant prognostic factors for disease-specific survival ( P < 0.0001 and P = 0.0477, respectively). Conclusions: The combination of PLR and LDH may be a potential biomarker for estimating disease-specific and overall survival in Japanese patients with metastatic RCC treated by nivolumab. If changes of inflammation-based prognostic scores in response to nivolumab treatment might be improved, nivolumab treatment should be continued.

Nomogram to predict survival of pulmonary large-cell neuroendocrine carcinoma after surgery

2020 ◽  
Author(s):  
Qian Huang ◽  
Jie Liu ◽  
Huifang Cai ◽  
Qi Zhang ◽  
Lina Wang
Keyword(s):  
Overall Survival ◽  
Regression Analysis ◽  
Prognostic Factors ◽  
Neuroendocrine Carcinoma ◽  
Cox Regression ◽  
Predictive Performance ◽  
Large Cell ◽  
Large Cell Neuroendocrine Carcinoma ◽  
Operating Characteristics ◽  
Cox Regression Analysis

Abstract Background Pulmonary large-cell neuroendocrine carcinoma (LCNEC) is a rare primary malignant tumor with a poor prognosis, and surgery is the main treatment. However, there are no effective predictive tools to assess the prognosis of postoperative patients. Our aim is to identify prognostic factors and construct nomogram to accurately assess prognosis. Methods Patients were identified in the Surveillance, Epidemiology, and End Results (SEER) database. Based on the results of Cox regression analysis, construct nomogram for predicting 1-, 3-, and 5-year survival. The predictive performance of nomogram was evaluated using the consistency index (C-index), the area under the receiver operating characteristics curve (AUC), and calibration plots. Results We finally screened 903 patients with pulmonary LCNEC who underwent surgery. The Cox regression analysis showed that age, SEER stage, T stage, N stage, M stage, tumor size, and chemotherapy were independent prognostic factors for overall survival (P<0.05). The C-index of the nomogram is 0.681 on the training cohort and 0.675 on the validation cohort. The AUC and calibration plots show that the nomogram has good performance. Conclusion We constructed and validated nomogram for predicting 1-, 3-, and 5-year survival of patients with pulmonary LCNEC after surgery. Our nomogram provides reference information for assessing the overall survival of these patients.

scholarly journals Predicting Prognosis In Primary Pulmonary Sarcoma Using A Clinical Nomogram Based On SEER Database

2022 ◽  
Author(s):  
Piao Shen ◽  
Yuzhen Zheng ◽  
Siyu Zhu ◽  
Xingping Yang ◽  
Jian Tan ◽  
...  
Keyword(s):  
Overall Survival ◽  
Prognostic Factors ◽  
High Risk ◽  
Cox Regression ◽  
Risk Group ◽  
Roc Curves ◽  
Training Group ◽  
High Risk Group ◽  
Seer Database ◽  
Pulmonary Sarcoma

Abstract Background: Primary pulmonary sarcoma (PPS) accounts for less than 1.1% of all pulmonary tumors. Few data outcomes are reported. This study aims to clarify the predictive value of clinicopathologic features on the overall survival (OS) of PPS patients.Methods: Patients with primary pulmonary sarcoma (PPS) were collected from the Surveillance, Epidemiology, and End Results (SEER) database (from 2000 to 2015) and divided randomly into training and validation cohorts at a ratio of 1:1. Univariate Cox analysis and the least absolute shrinkage and selection operator (LASSO) were implemented to identify prognostic factors related to overall survival of primary pulmonary sarcoma patients. Then, we performed multivariate Cox regression to establish a prognostic factors signature. The Kaplan- Meier (K-M) survival curves and time-dependent receiver operating characteristic (ROC) curves were plotted to estimate the prognostic power of the signature. In addition, multivariate Cox regression screened out independent prognostic factors and constructed a nomogram. Results: PPS patients with training group were divided into low- and high-risk group based on risk score, and high-risk group had a shorter survival time. The validation group got the same result. (P<0.001). On multivariate analysis of the training cohort, independent factors for survival were marriage, age, sex, grade, operation, metastasis and tumor size, which were all selected into the nomogram. The calibration curve and ROC plots for probability of 3-year and 5-year survival were in accord with prediction by nomogram and actual observation. And the C-index of the nomogram for predicting survival was 0.77 (95% CI, 0.74 to 0.80, P<0.05), which was statistically significant. Conclusion: We constructed a risk prognosis model based on PPS patients from SEER database. In addition, the construction of nomogram provides one more idea for clinical treatment.

Treatment of cancer of the anal canal. The Hamburg experience

2006 ◽  
Vol 24 (18_suppl) ◽  
pp. 14062-14062
Author(s):  
V. Rudat ◽  
S. Streller ◽  
D. Rades
Keyword(s):  
Overall Survival ◽  
Prognostic Factors ◽  
Anal Canal ◽  
Survival Data ◽  
Cox Regression ◽  
Haemoglobin Concentration ◽  
International Standards ◽  
Surgical Approaches ◽  
Rank Test ◽  
Cox Regression Analysis

14062 Background: To compare surgical and non-surgical treatment approaches for anal cancer and to identify prognostic factors. Methods: Survival data of 214 patients with cancer of the anal canal were reviewed who were referred for radiotherapy to the Department of Radiation Oncology of the University of Hamburg, Germany between 1/88 and 3/05. 75 patients received a definitive radiochemotherapy (RCT) with 5-FU and MMC according to international standards, 43 an operation followed by RCT (OP+RCT), 37 an operation followed by irradiation (OP+RT), 25 an irradiation alone (RT) and 34 an operation alone because they refused a planned adjuvant RCT or RT. The operations had been performed by different referring hospitals in and around Hamburg. Results: The median follow-up time of the living patients was 67 months (1–200 months). The 10 year overall survival rate for RCT was 0.62 (95%CI 0.46–0.77), for OP+RCT 0.65 (95%CI 0.47–0.83), for OP+RT 0.55 (95%CI 0.37–0.74), for OP alone 0.51 (95%CI 0.26–0.75) and for RT alone 0.27 (95%CI 0.05–0.48). There was no statistical difference between the overall survival of patients who received RCT, OP+RCT and OP+RT according to Kaplan Meier analysis (log rank test, p = 0.71). Cox regression analysis was used to examine the simultaneous influence of the prognostic factors T, N, age, haemoglobin concentration before radiotherapy, gender, and grading on the survival of patients who were treated with RCT. The model (p = 0.015) revealed T and N to be the only statistically significant prognostic factors. Conclusions: The different surgical and non-surgical approaches to treat cancer of the anal canal in Hamburg obviously reflect the individual preferences of the different physicians. Statistical analysis did not show a benefit of an OP added to RCT. Prognostic factors for survival after RCT were the T- and N-stage. No significant financial relationships to disclose.

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