Individualized prediction of colon cancer recurrence using a nomogram

Perineural Invasion is a Strong Prognostic Factor in Colorectal Cancer: A Systematic Review

Perineural invasion (PNI) is a possible route for metastatic spread in various cancer types, including colorectal cancer (CRC). PNI is linked to poor prognosis, but systematic analyses are lacking. This study systematically reviews the frequency and impact of PNI in CRC. A literature search was performed using PubMed database from inception to January 1, 2014. Data were analyzed using Review Manager 5.3. A quality assessment was performed on the basis of modified REMARK criteria. Endpoints were local recurrence (LR), 5-year disease-free survival (5yDFS), 5-year cancer-specific survival (5yCSS), and 5-year overall survival (5yOS). Meta-analysis was performed in terms of risk ratios (RR) and hazard ratios (HR) with 95% confidence interval (95% CI). In this meta-analysis, 58 articles with 22,900 patients were included. PNI was present in 18.2% of tumors. PNI is correlated with increased LR (RR 3.22, 95% CI, 2.33-4.44) and decreased 5yDFS (RR 2.35, 95% CI, 1.66-3.31), 5yCSS (RR 3.61, 95% CI, 2.76-4.72), and 5yOS (RR 2.09, 95% CI, 1.68-2.61). In multivariate analysis PNI remains an independent prognostic factor for 5yDFS, 5yCSS, and 5yOS (HR 2.35, 95% CI, 1.97-3.08; HR 1.91, 95% CI, 1.50-2.42; and HR 1.85, 95% CI, 1.63-2.12, respectively). We confirmed the strong impact of PNI for LR and survival in CRC. The prognostic value of PNI is similar to that of well-established prognostic factors as depth of invasion, differentiation grade, lymph node metastases, and lymphatic and extramural vascular invasion. Therefore, PNI should be one of the factors in the standardized reporting of CRC and might be considered a high-risk feature.

Validation of nomogram for disease free survival for colon cancer in UK population: A prospective cohort study

AIMS

To externally validate the MSKCC nomogram in a UK population, and determine if it could be used in our practice here in the UK.

METHODS

The colon cancer database from a district general hospital in England was used to extract all patients who had a curative colon cancer resection. Inclusion criteria were all patients who had curative elective colon cancer resection between 01/01/1998 and 31/12/2003. Patients were followed up for up to ten years. Five and ten year predictions were calculated for each patient, and plotted against the actual recurrence using a ROC curve, and AUC was calculated for both the five and ten year nomogram.

RESULTS

138 patients were included in the study. Overall five year recurrence rate was 26.8% with a mean follow up of 60.24 months (SD = 38.6). 118 patients were included in the five year nomogram validation, and 102 patients were included in the ten year nomogram validation. A ROC curve was plotted for both the five and ten year nomogram and AUC was calculated. For the five year nomogram AUC was 0.673, and for the ten year nomogram AUC was 0.687. Two cut off points were identified for each nomogram and this divided the cohort into low, medium and high risk groups for recurrence. Cox regression showed there was significant difference between all groups for both nomograms.

CONCLUSION

The MSKCC colon cancer nomogram was validated in our cohort, but it is recommended to be used in conjunction with AJCC TNM staging system.

Predicting Individualized Postoperative Survival for Stage II/III Colon Cancer Using a Mobile Application Derived from the National Cancer Data Base

BACKGROUND

Prediction calculators estimate postoperative survival and assist the decision-making process for adjuvant treatment. The objective of this study was to create a postoperative overall survival (OS) calculator for patients with stage II/III colon cancer. Factors that influence OS, including comorbidity and postoperative variables, were included.

STUDY DESIGN

The National Cancer Data Base was queried for patients with stage II/III colon cancer, diagnosed between 2004 and 2006, who had surgical resection. Patients were randomly divided to a testing (nt) cohort comprising 80% of the dataset and a validation (nv) cohort comprising 20%. Multivariable Cox proportional hazards regression of nt was performed to identify factors associated with 5-year OS. These were used to build a prediction model. The performance was assessed using the nv cohort and translated into mobile software.

RESULTS

A total of 129,040 patients had surgery. After exclusion of patients with carcinoma in situ, nonadenocarcinoma histology, more than 1 malignancy, stage I or IV disease, or missing data, 34,176 patients were used in the development of the calculator. Independent predictors of OS included patient-specific characteristics, pathologic factors, and treatment options, including type of surgery and adjuvant therapy. Length of postoperative stay and unplanned readmission rates were also incorporated as surrogates for postoperative complications (1-day increase in postoperative stay, hazard ratio [HR] 1.019, 95% CI 1.018 to 1.021, p < 0.001; unplanned readmission vs no readmission HR 1.35, 95% CI 1.25 to 1.45, p < 0.001). Predicted and actual 5-year OS rates were compared in the nv cohort with 5-year area under the curve of 0.77.

CONCLUSIONS

An individualized, postoperative OS calculator application was developed for patients with stage II/III colon cancer. This prediction model uses nationwide data, culminating in a highly comprehensive, clinically useful tool.

Standardized data collection to build prediction models in oncology: a prototype for rectal cancer

The advances in diagnostic and treatment technology are responsible for a remarkable transformation in the internal medicine concept with the establishment of a new idea of personalized medicine. Inter- and intra-patient tumor heterogeneity and the clinical outcome and/or treatment's toxicity's complexity, justify the effort to develop predictive models from decision support systems. However, the number of evaluated variables coming from multiple disciplines: oncology, computer science, bioinformatics, statistics, genomics, imaging, among others could be very large thus making traditional statistical analysis difficult to exploit. Automated data-mining processes and machine learning approaches can be a solution to organize the massive amount of data, trying to unravel important interaction. The purpose of this paper is to describe the strategy to collect and analyze data properly for decision support and introduce the concept of an 'umbrella protocol' within the framework of 'rapid learning healthcare'.

Adjuvant chemotherapy for rectal cancer: Is it needed?

Adjuvant chemotherapy has become a standard treatment of advanced rectal cancer in the West. The benefits of adjuvant chemotherapy after surgery alone have been well established. However, controversy surrounds the use adjuvant chemotherapy in patients who received preoperative chemoradiotherapy, despite it being recommended by a number of international guidelines. Results of recent multicentre randomised control trials showed no benefit of adjuvant chemotherapy in terms of survival and rates of distant metastases. However, concerns exist regarding the quality of the studies including inadequate staging modalities, out-dated chemotherapeutic regimens and surgical approaches and small sample sizes. It has become evident that not all the patients respond to adjuvant chemotherapy and more personalised approach should be employed when considering the benefits of adjuvant chemotherapy. The present review discusses the strengths and weaknesses of the current evidence-base and suggests improvements for future studies.

Risk Prediction Tools in Oncology

Cancer prediction tools are widely available to clinicians, and the data retrieved from these tools can assist with patient counseling sessions on risk, prognosis, treatment, and recurrence. Current tools are able to synthesize data in a concise, unbiased, and evidence-based method, allowing patients to make better-informed decisions about their treatment options. As useful as these tools can be, clinicians must understand their limitations and evaluate the tools for quality and applicability.
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Nomograms for predicting survival and recurrence in patients with adenoid cystic carcinoma. An international collaborative study

BACKGROUND

Due to the rarity of adenoid cystic carcinoma (ACC), information on outcome is based upon small retrospective case series. The aim of our study was to create a large multiinstitutional international dataset of patients with ACC in order to design predictive nomograms for outcome.

METHODS

ACC patients managed at 10 international centers were identified. Patient, tumor, and treatment characteristics were recorded and an international collaborative dataset created. Multivariable competing risk models were then built to predict the 10 year recurrence free probability (RFP), distant recurrence free probability (DRFP), overall survival (OS) and cancer specific mortality (CSM). All predictors of interest were added in the starting full models before selection, including age, gender, tumor site, clinical T stage, perineural invasion, margin status, pathologic N-status, and M-status. Stepdown method was used in model selection to choose predictive variables. An external dataset of 99 patients from 2 other institutions was used to validate the nomograms.

FINDINGS

Of 438 ACC patients, 27.2% (119/438) died from ACC and 38.8% (170/438) died of other causes. Median follow-up was 56 months (range 1-306). The nomogram for OS had 7 variables (age, gender, clinical T stage, tumor site, margin status, pathologic N-status and M-status) with a concordance index (CI) of 0.71. The nomogram for CSM had the same variables, except margin status, with a concordance index (CI) of 0.70. The nomogram for RFP had 7 variables (age, gender, clinical T stage, tumor site, margin status, pathologic N status and perineural invasion) (CI 0.66). The nomogram for DRFP had 6 variables (gender, clinical T stage, tumor site, pathologic N-status, perineural invasion and margin status) (CI 0.64). Concordance index for the external validation set were 0.76, 0.72, 0.67 and 0.70 respectively.

INTERPRETATION

Using an international collaborative database we have created the first nomograms which estimate outcome in individual patients with ACC. These predictive nomograms will facilitate patient counseling in terms of prognosis and subsequent clinical follow-up. They will also identify high risk patients who may benefit from clinical trials on new targeted therapies for patients with ACC.

FUNDING

None.

Nomograms for colorectal cancer: A systematic review

AIM

To assist in the selection of suitable nomograms for obtaining desired predictions in daily clinical practice.

METHODS

We conducted electronic searches for journal articles on colorectal cancer (CRC)-associated nomograms using the search terms colon/rectal/colorectal/nomogram. Of 174 articles initially found, we retrieved 28 studies in which a nomogram for CRC was developed.

RESULTS

We discuss the currently available CRC-associated nomograms, including those that predict the oncological prognosis, the short-term outcome of treatments, such as surgery or neoadjuvant chemoradiotherapy, and the future development of CRC. Developing nomograms always presents a dilemma. On the one hand, the desire to cover as wide a patient range as possible tends to produce nomograms that are too complex and yet have C-indexes that are not sufficiently high. Conversely, confining the target patients might impair the clinical applicability of constructed nomograms.

CONCLUSION

The information provided in this review should be of use in selecting a nomogram suitable for obtaining desired predictions in daily clinical practice.

GATA2 rs2335052 Polymorphism Predicts the Survival of Patients with Colorectal Cancer

Background

GATA binding protein 2 (GATA2) is a transcription factor that has essential roles in hematologic malignancies and progression of various solid tumors. Our previous studies suggested that high GATA2 expression is associated with recurrence of colorectal cancer (CRC). However, the influence of GATA2 single nucleotide polymorphisms (SNPs) on the survival of CRC remains unknown.

Methods

We genotyped GATA2 SNP rs2335052 using Sanger sequencing after PCR amplification, and determined GATA2 expression by immunohistochemistry in a cohort of 180 CRC patients. Kaplan-Meier survival analysis and Cox proportional hazard regression were used to analyze the association between the GATA2 rs2335052 genotypes and the clinical outcome of CRC.

Results

We found that there was no significant correlation between the rs2335052 genotypes and the expression of GATA2. However, the Kaplan-Meier survival analysis suggested that the carriers of the A-allele of SNP rs2335052 were significantly associated with increased risk of recurrence and reduced disease-free survival (DFS), compared with those carrying the variant genotype of GG in rs2335052 (P = 0.021). Moreover, univariate and multivariate Cox regression analyses revealed that GATA2 SNP rs2335052 was an independent risk factor for the DFS of CRC patients.

Conclusion

Our results demonstrated that GATA2 SNP rs2335052 is an independent predictor for prognosis of CRC patients. This raised the possibility that SNP rs2335052 may serve as a potential indicator for predicting recurrence of CRC after curative colectomy.

Nomograms in oncology: more than meets the eye

Nomograms are widely used as prognostic devices in oncology and medicine. With the ability to generate an individual probability of a clinical event by integrating diverse prognostic and determinant variables, nomograms meet our desire for biologically and clinically integrated models and fulfill our drive towards personalised medicine. Rapid computation through user-friendly digital interfaces, together with increased accuracy, and more easily understood prognoses compared with conventional staging, allow for seamless incorporation of nomogram-derived prognosis to aid clinical decision making. This has led to the appearance of many nomograms on the internet and in medical journals, and an increase in nomogram use by patients and physicians alike. However, the statistical foundations of nomogram construction, their precise interpretation, and evidence supporting their use are generally misunderstood. This issue is leading to an under-appreciation of the inherent uncertainties regarding nomogram use. We provide a systematic, practical approach to evaluating and comprehending nomogram-derived prognoses, with particular emphasis on clarifying common misconceptions and highlighting limitations.

Validation of the Memorial Sloan-Kettering Cancer Center Nomogram to Predict Overall Survival After Curative Colectomy in a Chinese Colon Cancer Population

BACKGROUND

Colon cancer nomogram designed by Memorial Sloan-Kettering Cancer Center (MSKCC) is an online prediction tool to predict overall survival for individual patient after curative resection. However, this model was never externally validated. We evaluated the accuracy of this nomogram in an independent external Chinese cohort.

METHODS

Clinical data from 1005 patients who underwent primary curative-intent surgery at Peking University Cancer Hospital & Institute between 1996 and 2008 were used for external validation. Clinicopathologic characteristics and the performance of the MSKCC nomogram for prediction of overall survival were evaluated for 985 patients with complete data by using concordance index (C-index) and calibration plot.

RESULTS

The C-index for the MSKCC nomogram was 0.71 in the Chinese cohort, compared with 0.67 for American Joint Committee on Cancer (AJCC) stage (P < .0001). This suggests that the nomogram discriminates overall survival better than AJCC staging system. Calibration plot showed a good calibration of the nomogram in the validation cohort. Furthermore, the MSKCC nomogram prediction illustrated the heterogeneity for survival of Chinese patients within each AJCC stage.

CONCLUSIONS

The MSKCC nomogram for colon cancer provides more accurate survival predictions than the AJCC staging system when applied to an external Chinese cohort. The MSKCC nomogram improved individualized prediction of survival and may aid in more accurate patient counseling, selection of various treatment options, and follow-up scheduling.

The impact of neural invasion severity in gastrointestinal malignancies: a clinicopathological study

OBJECTIVES

Because neural invasion (NI) is still inconsistently reported and not well characterized within gastrointestinal malignancies (GIMs), our aim was to determine the exact prevalence and severity of NI and to elucidate the true impact of NI on patient's prognosis.

BACKGROUND

The union internationale contre le cancer (UICC) recently added NI as a novel parameter in the current TNM classification. However, there are only a few existing studies with specific focus on NI, so that the distinct role of NI in GIMs is still uncertain.

MATERIALS AND METHODS

NI was characterized in approximately 16,000 hematoxylin and eosin tissue sections from 2050 patients with adenocarcinoma of the esophagogastric junction (AEG)-I-III, squamous cell carcinoma (SCC) of the esophagus, gastric cancer (GC), colon cancer (CC), rectal cancer (RC), cholangiocellular cancer (CCC), hepatocellular cancer (HCC), and pancreatic cancer (PC). NI prevalence and severity was determined and related to patient's prognosis and survival.

RESULTS

NI prevalence largely varied between HCC/6%, CC/28%, RC/34%, AEG-I/36% and AEG-II/36%, SCC/37%, GC/38%, CCC/58%, and AEG-III/65% to PC/100%. NI severity score was uppermost in PC (24.9±1.9) and lowest in AEG-I (0.8±0.3). Multivariable analyses including age, sex, TNM stage, and grading revealed that the prevalence of NI was significantly associated with diminished survival in AEG-II/III, GC, and RC. However, increasing NI severity impaired survival in AEG-II/III and PC only.

CONCLUSIONS

NI prevalence and NI severity strongly vary within GIMs. Determination of NI severity in GIMs is a more precise tool than solely recording the presence of NI and revealed dismal prognostic impact on patients with AEG-II/III and PC. Evidently, NI is not a concomitant side feature in GIMs and, therefore, deserves special attention for improved patient stratification and individualized therapy after surgery.

Validation of a nomogram for predicting the probability of carcinoma in patients with intraductal papillary mucinous neoplasm in 180 pancreatic resection patients at 3 high-volume centers

OBJECTIVE

We previously published a nomogram for prediction of carcinoma in patients with intraductal papillary mucinous neoplasm (IPMN). The objective of the current study was to validate this nomogram in an external cohort of patients at multiple institutions.

METHODS

The clinical details of 180 patients with IPMN who underwent a pancreatic resection at 3 hospitals were collected. Four significant predictive factors (sex, lesion type, nodule height, and pancreatic juice cytology) were analyzed.

RESULTS

Of the 180 patients, 66 (36.7%) had a main pancreatic duct-type IPMN and 114 (63.3%) had a branch pancreatic duct-type IPMN. The final pathological diagnosis was benign IPMN in 95 (52.8%) patients and malignant IPMN in 85 (47.2%) patients. The area under the receiver operating characteristic curve for the model was 0.760. The area under the receiver operating characteristic curve of the IPMN nomogram for prediction of malignancy was 0.747 in main pancreatic duct-type IPMN and 0.752 in branch pancreatic duct-type IPMN. The sensitivity and specificity of the model were 80.0% and 57.9%, respectively, when the predictive probability of more than 10% was used to indicate the presence of carcinoma.

CONCLUSIONS

This nomogram for predicting the probability of carcinoma in patients with IPMN was accurate in an external validation patient cohort.

Postoperative Nomogram for Predicting Cancer-Specific Mortality in Medullary Thyroid Cancer

BACKGROUND

Medullary thyroid cancer (MTC) is a rare thyroid cancer accounting for 5 % of all thyroid malignancies. The purpose of our study was to design a predictive nomogram for cancer-specific mortality (CSM) utilizing clinical, pathological, and biochemical variables in patients with MTC.

METHODS

MTC patients managed entirely at Memorial Sloan-Kettering Cancer Center between 1986 and 2010 were identified. Patient, tumor, and treatment characteristics were recorded, and variables predictive of CSM were identified by univariable analyses. A multivariable competing risk model was then built to predict the 10-year cancer specific mortality of MTC. All predictors of interest were added in the starting full model before selection, including age, gender, pre- and postoperative serum calcitonin, pre- and postoperative CEA, RET mutation status, perivascular invasion, margin status, pathologic T status, pathologic N status, and M status. Stepdown method was used in model selection to choose predictive variables.

RESULTS

Of 249 MTC patients, 22.5 % (56/249) died from MTC, whereas 6.4 % (16/249) died secondary to other causes. Mean follow-up period was 87 ± 67 months. The seven variables with the highest predictive accuracy for cancer specific mortality included age, gender, postoperative calcitonin, perivascular invasion, pathologic T status, pathologic N status, and M status. These variables were used to create the final nomogram. Discrimination from the final nomogram was measured at 0.77 with appropriate calibration.

CONCLUSIONS

We describe the first nomogram that estimates cause-specific mortality in individual patients with MTC. This predictive nomogram will facilitate patient counseling in terms of prognosis and subsequent clinical follow up.

Presence of lymphovascular invasion in urothelial bladder cancer specimens after transurethral resections correlates with risk of upstaging and survival: a systematic review and meta-analysis

OBJECTIVES

This study aimed to elucidate the relationship between lymphovascular invasion (LVI) at transurethral resection of bladder tumor (TURBT) and the risk of pathologic upstaging as well as the clinical outcomes.

MATERIALS AND METHODS

PubMed, Scopus, Web of Science, and Cochrane Library databases were searched from the respective dates of inception until November 11, 2013.

RESULTS

A total of 16 articles met the eligibility criteria for this systematic review, which included a total of 3,905 patients. LVI was detected in 18.6% of TURBT specimens. A significant association was found between LVI at TURBT and pathologic upstaging of bladder cancer (odds ratio = 2.21, 95% CI: 1.44-3.39) without heterogeneity (I(2) = 45%, P = 0.14). The pooled hazard ratio (HR) was statistically significant for recurrence-free survival (HR = 1.47, 95% CI: 1.24-1.74), progression-free survival (HR = 2.28, 95% CI: 1.45-3.58), and disease-specific survival (HR = 1.35, 95% CI: 1.01-1.81), but not for overall survival (HR = 1.55, 95% CI: 0.90-2.67). Tests of inconsistency for disease-specific survival (I(2) = 66%, P = 0.007) and overall survival (I(2) = 72%, P = 0.03) could not exclude a significant heterogeneity. The results of the Begg and the Egger tests showed that there was evidence of publication bias on pathologic upstaging and progression-free survival.

CONCLUSIONS

The data obtained in this meta-analysis indicate that the presence of LVI at TURBT portends the increased risk of pathologic upstaging and may provide additional prognostic information. However, a large, well-designed, prospective study is needed to investigate potential treatment options for bladder cancer with LVI.

ACCENT-based web calculators to predict recurrence and overall survival in stage III colon cancer

BACKGROUND

Current prognostic tools in colon cancer use relatively few patient characteristics. We constructed and validated clinical calculators for overall survival (OS) and time to recurrence (TTR) for stage III colon cancer and compared their performance against an existing tool (Numeracy) and American Joint Committee on Cancer (AJCC) version 7 staging.

METHODS

Data from 15936 stage III patients accrued to phase III clinical trials since 1989 were used to construct Cox models for TTR and OS. Variables included age, sex, race, body mass index, performance status, tumor grade, tumor stage, ratio of positive lymph nodes to nodes examined, number and location of primary tumors, and adjuvant treatment (fluoropyrimidine single agent or in combination). Missing data were imputed, and final models internally validated for optimism-corrected calibration and discrimination and compared with AJCC. External validation and comparisons against Numeracy were performed using stage III patients from NSABP trial C-08. All statistical tests were two-sided.

RESULTS

All variables were statistically and clinically significant for OS prediction, while age and race did not predict TTR. No meaningful interactions existed. Models for OS and TTR were well calibrated and associated with C-indices of 0.66 and 0.65, respectively, compared with C-indices of 0.58 and 0.59 for AJCC. These tools, available online, better predicted patient outcomes than Numeracy, both overall and within patient subgroups, in external validation.

CONCLUSIONS

The proposed ACCENT calculators are internally and externally valid, better discriminate patient risk than AJCC version 7 staging, and better predict patient outcomes than Numeracy. These tools have replaced Numeracy for online clinical use and will aid prognostication and patient/physician communication.

Controversies in the pathological assessment of colorectal cancer

Pathologic assessment of colorectal cancer specimens plays an essential role in patient management, informing prognosis and contributing to therapeutic decision making. The tumor-node-metastasis (TNM) staging system is a key component of the colorectal cancer pathology report and provides important prognostic information. However there is significant variation in outcome of patients within the same tumor stage. Many other histological features such as tumor budding, vascular invasion, perineural invasion, tumor grade and rectal tumor regression grade that may be of prognostic value are not part of TNM staging. Assessment of extramural tumor deposits and peritoneal involvement contributes to TNM staging but there are some difficulties with the definition of both of these features. Controversies in colorectal cancer pathology reporting include the subjective nature of some of the elements assessed, poor reporting rates and reproducibility and the need for standardized examination protocols and reporting. Molecular pathology is becoming increasingly important in prognostication and prediction of response to targeted therapies but accurate morphology still has a key role to play in colorectal cancer pathology reporting.

Outcomes in non-metastatic colorectal cancer

The measurement of outcomes in non-metastatic colon and rectal cancer patients is a multi-dimensional endeavor involving prediction tools, standard of care, and best treatment guidelines. Socioeconomic, demographic, and racial impacts on outcome must be carefully considered. Consideration must also be given to measures of cost, quality, and healthcare delivery in response to initiatives meant to optimize patient health while maintaining quality of life.

MicroRNA profiles discriminate among colon cancer metastasis

MicroRNAs are being exploited for diagnosis, prognosis and monitoring of cancer and other diseases. Their high tissue specificity and critical role in oncogenesis provide new biomarkers for the diagnosis and classification of cancer as well as predicting patients' outcomes. MicroRNAs signatures have been identified for many human tumors, including colorectal cancer (CRC). In most cases, metastatic disease is difficult to predict and to prevent with adequate therapies. The aim of our study was to identify a microRNA signature for metastatic CRC that could predict and differentiate metastatic target organ localization. Normal and cancer tissues of three different groups of CRC patients were analyzed. RNA microarray and TaqMan Array analysis were performed on 66 Italian patients with or without lymph nodes and/or liver recurrences. Data obtained with the two assays were analyzed separately and then intersected to identify a primary CRC metastatic signature. Five differentially expressed microRNAs (hsa-miR-21, -103, -93, -31 and -566) were validated by qRT-PCR on a second group of 16 American metastatic patients. In situ hybridization was performed on the 16 American patients as well as on three distinct commercial tissues microarray (TMA) containing normal adjacent colon, the primary adenocarcinoma, normal and metastatic lymph nodes and liver. Hsa-miRNA-21, -93, and -103 upregulation together with hsa-miR-566 downregulation defined the CRC metastatic signature, while in situ hybridization data identified a lymphonodal invasion profile. We provided the first microRNAs signature that could discriminate between colorectal recurrences to lymph nodes and liver and between colorectal liver metastasis and primary hepatic tumor.

Predictors of recurrence free survival for patients with stage II and III colon cancer

Background

The aim of this study was to evaluate clinico-pathologic specific predictors of recurrence for stage II/III disease. Improving recurrence prediction for resected stage II/III colon cancer patients could alter surveillance strategies, providing opportunities for more informed use of chemotherapy for high risk individuals.

Methods

871 stage II and 265 stage III patients with colon cancers were included. Features studied included surgery date, age, gender, chemotherapy, tumor location, number of positive lymph nodes, tumor differentiation, and lymphovascular and perineural invasion. Time to recurrence was evaluated, using Cox’s proportional hazards models. The predictive ability of the multivariable models was evaluated using the concordance (c) index.

Results

For stage II cancer patients, estimated recurrence-free survival rates at one, three, five, and seven years following surgery were 98%, 92%, 90%, and 89%. Only T stage was significantly associated with recurrence. Estimated recurrence-free survival rates for stage III patients at one, three, five, and seven years following surgery were 94%, 78%, 70%, and 66%. Higher recurrence rates were seen in patients who didn’t receive chemotherapy (p = 0.023), with a higher number of positive nodes (p < 0.001). The c-index for the stage II model was 0.55 and 0.68 for stage III.

Conclusions

Current clinic-pathologic information is inadequate for prediction of colon cancer recurrence after resection for stage II and IIII patients. Identification and clinical use of molecular markers to identify the earlier stage II and III colon cancer patients at elevated risk of recurrence are needed to improve prognostication of early stage colon cancers.

Individualized prediction of risk of metachronous peritoneal carcinomatosis from colorectal cancer

AIM

The purpose of the study was to develop a tool for predicting the individual risk of metachronous peritoneal carcinomatosis after surgery for non-metastatic colorectal cancer.

METHOD

Independent predictors for metachronous colorectal carcinomatosis have previously been identified using a population-based database. Predictive models for colon and rectal cancer were developed from these data. The predictive models were based on multivariable Cox proportional hazard regression and were internally validated with bootstrapping. Performance was assessed by the concordance index and calibration plots.

RESULTS

In all, 8044 patients who underwent abdominal resection of colorectal cancer Stage I-III were included. The colon and rectal cancer risk score models predicted metachronous peritoneal carcinomatosis with a concordance index of 80% and 78%, respectively. Factors in the models included age, pathological pT stage, pN stage, number of examined lymph nodes (0-11, 12+), type of surgery (emergency/elective), completeness of cancer resection (R0/R1/R2), adjuvant chemotherapy (yes/no), preoperative radiotherapy and tumour location.

CONCLUSION

The proposed predictive models showed high internal validity and enabled individualized prediction of peritoneal recurrence of colorectal cancer. The models may help in the planning of treatment and follow-up of patients. However, external validation is warranted to assess generalizability of the predicted absolute risks.

Can long-term follow-up strategies be determined using a nomogram-based prediction model of malignancy among intraductal papillary mucinous neoplasms of the pancreas?

OBJECTIVES

This study investigated whether a risk assessment nomogram can predict the malignant potential of intraductal papillary mucinous neoplasms (IPMNs) and provide valuable information for the follow-up and counseling strategies of such patients.

METHODS

We studied 126 of 589 patients with IPMN who were followed up for at least 36 months with annual endoscopic ultrasonography. We analyzed scores derived from our nomogram, incorporating the parameters of sex, lesion type, mural nodule height, and pancreatic juice cytology determined at the initial IPMN evaluation.

RESULTS

The rate of malignant IPMNs was 5.5% (7/126). The initial average nomogram score was 19.8 (range, 0-55), and the final follow-up average was 23.8 (range, 0-109). When a cutoff score was set at 35 points, the sensitivity, specificity, and accuracy of the nomogram to assess malignancy risk were 87.5%, 96.6%, and 96%, respectively. The area under the receiver operating characteristic curve of malignant IPMN prediction during follow-up was 0.865.

CONCLUSIONS

The ability of the nomogram to predict malignancy in patients with IPMN was validated. Our findings can suggest that a follow-up for patients at high and low risk for cancer progression could be scheduled every 3 to 6 and 12 months, respectively.

Future directions for the early detection of colorectal cancer recurrence

Surgical resection remains a mainstay of treatment and is highly effective for localized colorectal cancer. However, ~30-40% of patients develop recurrence following surgery and 40-50% of recurrences are apparent within the first few years after initial surgical resection. Several variables factor into the ultimate outcome of these patients, including the extent of disease, tumor biology, and patient co-morbidities. Additionally, the time from initial treatment to the development of recurrence is strongly associated with overall survival, particularly in patients who recur within one year of their surgical resection. Current post-resection surveillance strategies involve physical examination, laboratory, endoscopic and imaging studies utilizing various high and low-intensity protocols. Ultimately, the goal is to detect recurrence as early as possible, and ideally in the asymptomatic localized phase, to allow initiation of treatment that may still result in cure. While current strategies have been effective, several efforts are evolving to improve our ability to identify recurrent disease at its earliest phase. Our aim with this article is to briefly review the options available and, more importantly, examine emerging and future options to assist in the early detection of colon and rectal cancer recurrence.

Analysis of the quality of care in surgical treatment of colorectal cancer: national study. Follow-up results

OBJECTIVES

Using the cases included in the Study on the quality of care in colorectal cancer conducted by the Spanish Association of Surgeons in 2008, we present follow-up data.

METHOD

Multicenter, descriptive, longitudinal and prospective study of patients operated on a scheduled basis of colorectal cancer. 35 hospitals have contributed data on 334 patients. Follow-up data: survival, recurrence and complications.

RESULTS

Mean follow-up was 28.61±11.32 months. Follow-up by surgeon: 69.2%, tumor recurrence 23.6%, in 83.3% it was systemic; 28.2% underwent salvage surgery. Overall survival was 76.6%, disease-free survival 65.6% (26.49±11.90 months). Tumor related mortality was 12,6%. Percentage of ventral hernias was 5.8%, intestinal obstruction 3.5%.

CONCLUSIONS

Quality and results of follow-up of patients operated on for CRC in Spain are similar to those reported in the Scientific literature. Areas for improvement: follow-up, earlier diagnosis, increase adjuvant and neoadjuvant treatments and total mesorectal excision as standard surgery for rectal cancer.

A pre-operative nomogram for decision making in oncological surgical emergencies

BACKGROUND

The purpose of the study was to propose a clinical decision-making tool for predicting mortality in patients undergoing emergency abdominal surgery with a palliative intent in the oncology setting.

METHODS

Identification of all emergency surgical procedures performed in a Department of Oncologic Surgery in a Comprehensive Cancer Center between January 2008 and January 2013. Multivariate logistic and Cox regression models were used to identify factors predicitve of mortality at 3 months and survival probabilities. Models were internally validated using bootstrapping and calibration.

RESULTS

The mortality rates were 30% at 1 month, 46.7% at 3 months and 83.3% at the end of the study. One model based on the albumin level and the P-POSSUM score (AUC: 0.725) adequately predicted mortality at 3 months. A survival nomogram predicted mortality with a concordance index (CI) of 0.718, using the following factors: WHO performance status (P = 0.02), albumin level (P < 0.01) and P-POSSUM score (P < 0.01). The origin or the extent of the carcinoma did not own sufficient pronostic impact to be selected in this model.

CONCLUSIONS

Pre-operative mortality risk scores can be developed in a palliative context. Physicians counselling and surgical decision making should be based on the use of these tools.

Follow-up after curative resection of colorectal cancer

Of the 13.7 million cancer survivors living in the United States as of January 2012, 1.2 million, or 9 %, were colorectal cancer (CRC) survivors. Determining an optimal surveillance for CRC survivors is necessary because of the significant burden follow-up poses to patients, physicians, and the health care system. Currently, there is no consensus regarding optimal follow-up in CRC patients. Current literature and published guidelines related to CRC follow-up were reviewed to examine the evidence for the surveillance strategies and specific tools demonstrated to improve outcome after curative CRC resection. An intensive surveillance strategy results in increased identification of recurrences amenable to curative resection but does not result in reduced overall or CRC-specific mortality. Patients most likely to benefit from surveillance include younger patients, those with earlier tumors, locoregional recurrences, longer time to recurrence, lower carcinoembryonic antigen (CEA) levels before reoperation, and those with isolated recurrence. Complete resection of recurrence is the only factor consistently associated with improved survival. CEA, colonoscopy, and liver-focused imaging surveillance appear to have the greatest impact on mortality after curative CRC resection. A CRC surveillance strategy is recommended that includes tumor risk stratification, that provides a focus on identifying recurrences amenable to complete resection, and that utilizes those modalities demonstrated to be most effective at improving outcome after CRC resection.

Nomogram prediction of survival and recurrence in patients with extrahepatic bile duct cancer undergoing curative resection followed by adjuvant chemoradiation therapy

PURPOSE

To develop nomograms for predicting the overall survival (OS) and relapse-free survival (RFS) in patients with extrahepatic bile duct cancer undergoing adjuvant chemoradiation therapy after curative resection.

METHODS AND MATERIALS

From January 1995 through August 2006, a total of 166 consecutive patients underwent curative resection followed by adjuvant chemoradiation therapy. Multivariate analysis using Cox proportional hazards regression was performed, and this Cox model was used as the basis for the nomograms of OS and RFS. We calculated concordance indices of the constructed nomograms and American Joint Committee on Cancer (AJCC) staging system.

RESULTS

The OS rate at 2 years and 5 years was 60.8% and 42.5%, respectively, and the RFS rate at 2 years and 5 years was 52.5% and 38.2%, respectively. The model containing age, sex, tumor location, histologic differentiation, perineural invasion, and lymph node involvement was selected for nomograms. The bootstrap-corrected concordance index of the nomogram for OS and RFS was 0.63 and 0.62, respectively, and that of AJCC staging for OS and RFS was 0.50 and 0.52, respectively.

CONCLUSIONS

We developed nomograms that predicted survival and recurrence better than AJCC staging. With caution, clinicians may use these nomograms as an adjunct to or substitute for AJCC staging for predicting an individual's prognosis and offering tailored adjuvant therapy.

The PIRO (predisposition, insult, response, organ dysfunction) model: toward a staging system for acute illness

Multimodal therapy for diseases like cancer has only become practicable following the development of staging systems like the TNM (tumor, nodes, metastases) system. Staging enables the identification of subgroups of patients with a disease who not only have a differing prognosis, but who are also more likely to benefit from a specific therapeutic modality. Critically ill patients represent a highly heterogeneous population for whom multiple therapeutic options are potentially available, each carrying not only the potential for differential benefit, but also the potential for differential harm. The PIRO system (predisposition, insult, response, organ dysfunction) is a template proposal for a staging system for acute illness that incorporates assessment of pre-morbid baseline susceptibility (predisposition), the specific disorder responsible for acute illness (insult), the response of the host to that insult, and the resulting degree of organ dysfunction. However the creation of a valid, robust, and clinically useful system presents significant challenges arising from the complexity of the disease state, the lack of a clear phenotype, the confounding influence of the effects of therapy and of cultural and socio-economic factors, and the relatively low profile of acute illness with clinicians and the general public. This review summarizes the rationale for such a model of illness stratification and the results of preliminary cohort studies testing the concept. It further proposes two strategies for building a staging system, recognizing that this will be a demanding undertaking that will require decades of work.

Validation of the memorial Sloan-Kettering Cancer Center nomogram to predict disease-specific survival after R0 resection in a Chinese gastric cancer population

Background

Prediction of disease-specific survival (DSS) for individual patient with gastric cancer after R0 resection remains a clinical concern. Since the clinicopathologic characteristics of gastric cancer vary widely between China and western countries, this study is to evaluate a nomogram from Memorial Sloan-Kettering Cancer Center (MSKCC) for predicting the probability of DSS in patients with gastric cancer from a Chinese cohort.

Methods

From 1998 to 2007, clinical data of 979 patients with gastric cancer who underwent R0 resection were retrospectively collected from Peking University Cancer Hospital & Institute and used for external validation. The performance of the MSKCC nomogram in our population was assessed using concordance index (C-index) and calibration plot.

Results

The C-index for the MSKCC predictive nomogram was 0.74 in the Chinese cohort, compared with 0.69 for American Joint Committee on Cancer (AJCC) staging system (P<0.0001). This suggests that the discriminating value of MSKCC nomogram is superior to AJCC staging system for prognostic prediction in the Chinese population. Calibration plots showed that the actual survival of Chinese patients corresponded closely to the MSKCC nonogram-predicted survival probabilities. Moreover, MSKCC nomogram predictions demonstrated the heterogeneity of survival in stage IIA/IIB/IIIA/IIIB disease of the Chinese patients.

Conclusion

In this study, we externally validated MSKCC nomogram for predicting the probability of 5- and 9-year DSS after R0 resection for gastric cancer in a Chinese population. The MSKCC nomogram performed well with good discrimination and calibration. The MSKCC nomogram improved individualized predictions of survival, and may assist Chinese clinicians and patients in individual follow-up scheduling, and decision making with regard to various treatment options.

External validation of a prognostic nomogram for overall survival in women with uterine leiomyosarcoma

BACKGROUND

There is no validated system to identify prognostically distinct cohorts of women with uterine leiomyosarcoma (ULMS). By using an independent, pooled, multi-institutional, international patient cohort, the authors validated a recently proposed ULMS nomogram.

METHODS

The ULMS nomogram incorporated 7 clinical characteristics (age, tumor size, tumor grade, cervical involvement, locoregional metastases, distant metastases, and mitotic index (per 10 high-power fields) to predict overall survival (OS) after primary surgery. Independent cohorts from 2 sarcoma centers were included. Eligible women, at minimum, underwent a hysterectomy for primary, locally advanced, or metastatic ULMS and received part of their care at 1 of the centers between 1994 and 2010.

RESULTS

In total, 187 women with ULMS were identified who met the above criteria described above (median age, 51 years; median tumor size, 9 cm; median mitotic index, 20 per 10 high-power fields). Tumors generally were high grade (88%), FIGO stage I or II (61%) without cervical involvement (93%) and without locoregional metastases (77%) or distant metastases (83%). The median OS and the 5-year OS rate were 4.5 years (95% confidence interval, 3.2-5.3 years) and 46%, respectively; and 65 women (35%) remained alive at last follow-up. The nomogram concordance index was 0.67(standard error, 0.02), which was as high as the concordance index from the initial cohort used for nomogram development. The concordance between actual OS and nomogram predictions suggests excellent calibration because predictions were within 1% of actual 5-year OS rates for patients with a predicted 5-year OS of less than 0.68.

CONCLUSIONS

The ULMS nomogram was externally validated using independent cohorts. These findings support the international use of the ULMS nomogram prognostic of OS in ULMS.

The complexity of the count: considerations regarding lymph node evaluation in colorectal carcinoma

In patients with colorectal carcinoma, studies have reported improved survival with increasing numbers of retrieved lymph nodes. These findings are puzzling, as increased node sampling was not correlated with significant change in disease staging. Although the physiologic processes underlying this correlation between number of lymph nodes sampled and survival remain unknown, the reported correlation has caused modifications to clinical and non-clinical practices. Herein, we review the literature and discuss potential etiologies responsible for the observed increased survival statistics. Literature regarding colorectal lymph node anatomy, molecular aspects of colorectal cancer, changes in tumor characteristics and utilization of lymph node sample numbers are evaluated. In addition, we present the mathematical concepts available for probabilistic prediction of diagnostic confidence based upon sample size. From evaluation of the aggregate literature, certain facts emerge which are not easily identified within the individual studies. Colorectal carcinoma appears to encompass a number of individual disease entities with different physiologic characteristics and likelihoods of metastasis. In addition, it appears the improved survival is likely multifactorial including effects from intrinsic tumor biology and tumor-host interactions along with ever changing clinical practices. Finally, because lymph node count is dependent on a number of variables and is correlated, but unlikely to be causally associated with survival, use of this number as a quality indicator is unwarranted. Based on statistical considerations, the current recommended goal of 12-15 recovered lymph nodes without evidence of metastatic disease provides approximately 80% negative predictive value for colorectal carcinoma metastasis.

The severity of neural invasion is associated with shortened survival in colon cancer

PURPOSE

Neural invasion (NI) is a histopathologic feature of colon cancer that receives little consideration. Therefore, we conducted a morphologic and functional characterization of NI in colon cancer.

EXPERIMENTAL DESIGN

NI was investigated in 673 patients with colon cancer. Localization and severity of NI was determined and related to patient's prognosis and survival. The neuro-affinity of colon cancer cells (HT29, HCT-116, SW620, and DLD-1) was compared with pancreatic cancer (T3M4 and SU86.86) and rectal cancer cells (CMT-93) in the in vitro three-dimensional (3D)-neural-migration assay and analyzed via live-cell imaging. Immunoreactivity of the neuroplasticity marker GAP-43, and the neurotrophic-chemoattractant factors Artemin and nerve growth factor (NGF), was quantified in colon cancer and pancreatic cancer nerves. Dorsal root ganglia of newborn rats were exposed to supernatants of colon cancer, rectal cancer, and pancreatic cancer cells and neurite density was determined.

RESULTS

NI was detected in 210 of 673 patients (31.2%). Although increasing NI severity scores were associated with a significantly poorer survival, presence of NI was not an independent prognostic factor in colon cancer. In the 3D migration assay, colon cancer and rectal cancer cells showed much less neurite-targeted migration when compared with pancreatic cancer cells. Supernatants of pancreatic cancer and rectal cancer cells induced a much higher neurite density than those of colon cancer cells. Accordingly, NGF, Artemin, and GAP-43 were much more pronounced in nerves in pancreatic cancer than in colon cancer.

CONCLUSION

NI is not an independent prognostic factor in colon cancer. The lack of a considerable biologic affinity between colon cancer cells and neurons, the low expression profile of colonic nerves for chemoattractant molecules, and the absence of a major neuroplasticity in colon cancer may explain the low prevalence and impact of NI in colon cancer.

Clinical decision support and individualized prediction of survival in colon cancer: bayesian belief network model

BACKGROUND

We used a large population-based data set to create a clinical decision support system (CDSS) for real-time estimation of overall survival (OS) among colon cancer (CC) patients. Patients with CC diagnosed between 1969 and 2006 were identified from the Surveillance Epidemiology and End Results (SEER) registry. Low- and high-risk cohorts were defined. The tenfold cross-validation assessed predictive utility of the machine-learned Bayesian belief network (ml-BBN) model for clinical decision support (CDS).

METHODS

A data set consisting of 146,248 records was analyzed using ml-BBN models to provide CDS in estimating OS based on prognostic factors at 12-, 24-, 36-, and 60-month post-treatment follow-up.

RESULTS

Independent prognostic factors in the ml-BBN model included age, race; primary tumor histology, grade and location; Number of primaries, AJCC T stage, N stage, and M stage. The ml-BBN model accurately estimated OS with area under the receiver-operating-characteristic curve of 0.85, thereby improving significantly upon existing AJCC stage-specific OS estimates. Significant differences in OS were found between low- and high-risk cohorts (odds ratios for mortality: 17.1, 16.3, 13.9, and 8.8 for 12-, 24-, 36-, and 60-month cohorts, respectively).

CONCLUSIONS

A CDSS was developed to provide individualized estimates of survival in CC. This ml-BBN model provides insights as to how disease-specific factors influence outcome. Time-dependent, individualized mortality risk assessments may inform treatment decisions and facilitate clinical trial design.

Nomogram to predict the benefit of radiation for older patients with breast cancer treated with conservative surgery

PURPOSE

The role of radiation therapy (RT) after conservative surgery (CS) remains controversial for older patients with breast cancer. Guidelines based on recent clinical trials have suggested that RT may be omitted in selected patients with favorable disease. However, it is not known whether this recommendation should extend to other older women. Accordingly, we developed a nomogram to predict the likelihood of long-term breast preservation with and without RT.

METHODS

We used Surveillance, Epidemiology, and End Results-Medicare data to identify 16,092 women age 66 to 79 years treated with CS between 1992 and 2002, using claims to identify receipt of RT and subsequent mastectomy. Time to mastectomy was estimated using the Kaplan-Meier method. Cox proportional hazards models determined the effect of covariates on mastectomy-free survival (MFS). A nomogram was developed to predict 5- and 10-year MFS, given associated risk factors, and bootstrap validation was performed.

RESULTS

With a median follow-up of 7.2 years, the overall 5- and 10-year MFS rates were 98.1% (95% CI, 97.8% to 98.3%) and 95.4% (95% CI, 94.9% to 95.8%), respectively. In multivariate analysis, age, race, tumor size, estrogen receptor status, and receipt of RT were predictive of time to mastectomy and were incorporated into the nomogram. Nodal status was also included given a significant interaction with RT. The resulting nomogram demonstrated good accuracy in predicting MFS, with a bootstrap-corrected concordance index of 0.66.

CONCLUSION

This clinically useful tool predicts 5- and 10-year MFS among older women with early breast cancer using readily available clinicopathologic factors and can aid individualized clinical decision making by estimating predicted benefit from RT.

Generation and external validation of a tumor-derived 5-gene prognostic signature for recurrence of lymph node-negative, invasive colorectal carcinoma

BACKGROUND: One in 4 patients with lymph node-negative, invasive colorectal carcinoma (CRC) develops recurrent disease after undergoing curative surgery, and most die of advanced disease. Predicting which patients will develop a recurrence is a significantly growing, unmet medical need. METHODS: Archival formalin-fixed, paraffin-embedded (FFPE) primary adenocarcinoma tissues obtained at surgery were retrieved from 74 patients with CRC (15 with stage I disease and 59 with stage II disease) for Training/Test Sets. In addition, FFPE tissues were retrieved from 49 patients with stage I CRC and 215 patients with stage II colon cancer for an External Validation (EV) Set (n = 264) from 18 hospitals in 4 countries. No patients had received neoadjuvant/adjuvant therapy. Proprietary genetic programming analysis of expression profiles for 225 prespecified tumor genes was used to create a 36-month recurrence risk signature. RESULTS: Using reverse transcriptase-polymerase chain reaction, a 5-gene rule correctly classified 62 of 92 recurrent patients and 87 of 172 nonrecurrent patients in the EV Set (sensitivity, 0.67; specificity, 0.51). “High-risk” patients had a greater probability of 36-month recurrence (42%) than “low-risk” patients (26%; hazard ratio, 1.80; 95% confidence interval, 1.19-2.71; P = .007; Cox regression) independent of T-classification, the number of lymph nodes examined, histologic grade/subtype, anatomic location, age, sex, or race. The rule outperformed (P = .021) current National Comprehensive Cancer Network Guidelines (hazard ratio, 0.897). The same rule also differentiated the risk of recurrence (hazard ratio, 1.63; P = .031) in a subset of patients from the EV Set who had stage I/II colon cancer only (n = 251). CONCLUSIONS: To the authors' knowledge, the 5-gene rule (OncoDefender-CRC) is the first molecular prognostic that has been validated in both stage I CRC and stage II colon cancer. It outperforms standard clinicopathologic prognostic criteria and obviates the need to retrieve ≥12 lymph nodes for accurate prognostication. It identifies those patients most likely to develop recurrent disease within 3 years after curative surgery and, thus, those most likely to benefit from adjuvant treatment. Cancer 2012. © 2012 American Cancer Society.

Clinical decision support systems: potential with pitfalls

Clinical Decision Support Systems (CDSS), an important part of clinical practice, are comprised of a: knowledge base; program for integrating patient-specific information with the knowledge-base; and, user-interface to allow clinicians to interact with the system and get the right information needed to make the right decision for the right patient at the right time. We review the common approaches to CDSS, their strengths and weaknesses and how they are evaluated and developed for clinical use.

Deficient expression of DNA repair enzymes in early progression to sporadic colon cancer

Background

Cancers often arise within an area of cells (e.g. an epithelial patch) that is predisposed to the development of cancer, i.e. a "field of cancerization" or "field defect." Sporadic colon cancer is characterized by an elevated mutation rate and genomic instability. If a field defect were deficient in DNA repair, DNA damages would tend to escape repair and give rise to carcinogenic mutations.

Purpose

To determine whether reduced expression of DNA repair proteins Pms2, Ercc1 and Xpf (pairing partner of Ercc1) are early steps in progression to colon cancer.

Results

Tissue biopsies were taken during colonoscopies of 77 patients at 4 different risk levels for colon cancer, including 19 patients who had never had colonic neoplasia (who served as controls). In addition, 158 tissue samples were taken from tissues near or within colon cancers removed by resection and 16 tissue samples were taken near tubulovillous adenomas (TVAs) removed by resection. 568 triplicate tissue sections (a total of 1,704 tissue sections) from these tissue samples were evaluated by immunohistochemistry for 4 DNA repair proteins. Substantially reduced protein expression of Pms2, Ercc1 and Xpf occurred in field defects of up to 10 cm longitudinally distant from colon cancers or TVAs and within colon cancers. Expression of another DNA repair protein, Ku86, was infrequently reduced in these areas. When Pms2, Ercc1 or Xpf were reduced in protein expression, then either one or both of the other two proteins most often had reduced protein expression as well. The mean inner colon circumferences, from 32 resections, of the ascending, transverse and descending/sigmoid areas were measured as 6.6 cm, 5.8 cm and 6.3 cm, respectively. When combined with other measurements in the literature, this indicates the approximate mean number of colonic crypts in humans is 10 million.

Conclusions

The substantial deficiencies in protein expression of DNA repair proteins Pms2, Ercc1 and Xpf in about 1 million crypts near cancers and TVAs suggests that the tumors arose in field defects that were deficient in DNA repair and that deficiencies in Pms2, Ercc1 and Xpf are early steps, often occurring together, in progression to colon cancer.

Prediction of prognosis is not improved by the seventh and latest edition of the TNM classification for colorectal cancer in a single-center collective

OBJECTIVES

To compare the prognostic value of the sixth and seventh editions of the TNM classification, and of additional prognostic factors, in colorectal cancer.

BACKGROUND

The seventh TNM edition was released in 2009 with the aim of providing a more precise prediction of prognosis.

METHODS

Clinical and histopathological data of 2229 patients with colorectal cancer who underwent tumor resection between 1990 and 2006 were analyzed and compared by using the sixth and seventh editions of the TNM classification and a statistically calculated model of prognostic factors.

RESULTS

With the sixth edition, 5-year survival was 96% for stage I, 90% for IIA, 86% for IIB, 90% for IIIA, 72% for IIIB, 48% for IIIC, and 13% for IV. With the seventh edition, 5-year survival was 96% for stage I, 90% for IIA, 84% for IIB, 87% for IIC, 89% for IIIA, 72% for IIIB, 36% for IIIC, 15% for IVA, and 10% for IVB. The stage shifted for only 155 (7%) patients: from IIB to IIC (2%), from IIIB to IIIC (1%), and from IIIC to IIIA/B (4%). The performance of the seventh edition [concordance index (c-index) 0.83; 95% confidence interval (CI), 0.82-0.85] revealed no relevant improvement compared with the sixth edition (c-index 0.83; 95% CI, 0.82-0.84), or compared to a model based on independent prognostic factors (c-index 0.84; 95% CI, 0.83-0.86).

CONCLUSIONS

The seventh TNM edition did not provide greater accuracy in predicting colorectal cancer patients' prognosis but resulted in a more complex classification for daily clinical use.

Predicting survival after curative colectomy for cancer: individualizing colon cancer staging

PURPOSE

Cancer staging determines extent of disease, facilitating prognostication and treatment decision making. The American Joint Committee on Cancer (AJCC) TNM classification system is the most commonly used staging algorithm for colon cancer, categorizing patients on the basis of only these three variables (tumor, node, and metastasis). The purpose of this study was to extend the seventh edition of the AJCC staging system for colon cancer to incorporate additional information available from tumor registries, thereby improving prognostic accuracy.

METHODS

Records from 128,853 patients with primary colon cancer reported to the Surveillance, Epidemiology and End Results Program from 1994 to 2005 were used to construct and validate three survival models for patients with primary curative-intent surgery. Independent training/test data sets were used to develop and test alternative models. The seventh edition TNM staging system was compared with models supplementing TNM staging with additional demographic and tumor variables available from the registry by calculating a concordance index, performing calibration, and identifying the area under receiver operating characteristic (ROC) curves.

RESULTS

Inclusion of additional registry covariates improved prognostic estimates. The concordance index rose from 0.60 (95% CI, 0.59 to 0.61) for the AJCC model, with T- and N-stage variables, to 0.68 (95% CI, 0.67 to 0.68) for the model including tumor grade, number of collected metastatic lymph nodes, age, and sex. ROC curves for the extended model had higher sensitivity, at all values of specificity, than the TNM system; calibration curves indicated no deviation from the reference line.

CONCLUSION

Prognostic models incorporating readily available data elements outperform the current AJCC system. These models can assist in personalizing treatment and follow-up for patients with colon cancer.

Novel staging system for predicting disease-specific survival in patients with breast cancer treated with surgery as the first intervention: time to modify the current American Joint Committee on Cancer staging system

PURPOSE

American Joint Committee on Cancer (AJCC) staging is used to determine breast cancer prognosis, yet patient survival within each stage shows wide variation. We hypothesized that differences in biology influence this variation and that addition of biologic markers to AJCC staging improves determination of prognosis.

PATIENTS AND METHODS

We identified a cohort of 3,728 patients who underwent surgery as the first intervention between 1997 and 2006. A Cox proportional hazards model, with backward stepwise exclusion of factors and stratification on pathologic stage (PS), was used to test the significance of adding grade (G), lymphovascular invasion (L), estrogen receptor (ER) status (E), progesterone receptor (PR) status, combined ER and PR status (EP), or combined ER, PR, and human epidermal growth factor receptor 2 status (M). We assigned values of 0 to 2 to these disease-specific survival (DSS) -associated factors and assessed six different staging systems: PS, PS + G, PS + G L, PS + G E, PS + G EP, and PS + G M. We compared 5-year DSS rates, Akaike's information criterion (AIC), and Harrell's concordance index (C-index) between systems. Surveillance, Epidemiology, and End Results data were used as the external validation cohort (n = 26,711).

RESULTS

Median follow-up was 6.5 years, and 5-year DSS rate was 97.4%. The PS + G E status staging system was most precise, with a low AIC (1,931.9) and the highest C-index (0.80). PS + G E status was confirmed to stratify outcomes in internal bootstrapping samples and the external validation cohort.

CONCLUSION

Our results validate an improved breast cancer staging system that incorporates grade and ER status. We recommend that biologic markers be incorporated into revised versions of the AJCC staging system.

Clinical decision aids in colon cancer: a comparison of two predictive nomograms

BACKGROUND

The risk of recurrence of colon cancer after curative surgery can be estimated by using decision aids. These aids use pathologic and patient factors to predict recurrence risk after adjuvant chemotherapy and have been validated when using clinical trial populations; however, the performance of 2 decision aids were compared by using a cohort of patients treated at a single center.

PATIENTS AND METHODS

Patient data were used to estimate the risk of recurrence when using both the Adjuvant! for colon cancer and Memorial Sloan Kettering Cancer Center (MSKCC) decision aids. A receiver operator characteristic (ROC) curve analyzed the predicted chance of being disease free at 5 years against the actual outcome for each patient. This curve was then used to define cutoff points at a chosen sensitivity and specificity to stratify patients into risk groups, and survival curves for each group calculated.

RESULTS

Data on 134 patients were analyzed. The Pearson correlation between the 2 nomograms was 0.848 (P < .01). The ROC curve for the MSKCC nomogram had an area under the curve of 0.638. At a sensitivity and a specificity of 0.8, the MSKCC curve has a risk recurrence score of 69% and 84%, respectively. By using these cutoffs to stratify patients into 3 risk groups, a statistically significant difference in survival was found between high risk and low risk (P = .025).

CONCLUSION

Tools to predict risk or recurrence and estimate benefit from therapy may be enhanced in the future by using genetic profiling, but use of existing tools can help deliver a personalized approach to adjuvant therapy.

Perspectives on current tumor-node-metastasis (TNM) staging of cancers of the colon and rectum

Improvements in classifications of cancers based on discovery and validation of important histopathological parameters and new molecular markers continue unabated. Though still not perfect, recent updates of classification schemes in gastrointestinal oncology by the American Joint Commission on Cancer (tumor-node-metastasis [TNM] staging) and the World Health Organization further stratify patients and guide optimization of treatment strategies and better predict patient outcomes. These updates recognize the heterogeneity of patient populations with significant subgrouping of each tumor stage and use of tumor deposits to significantly "up-stage" some cancers; change staging parameters for subsets of IIIB and IIIC cancers; and introduce of several new subtypes of colon carcinomas. By the nature of the process, recent discoveries that are important to improving even routine standards of patient care, especially new advances in molecular medicine, are not incorporated into these systems. Nonetheless, these classifications significantly advance clinical standards and are welcome enhancements to our current methods of cancer reporting.

A novel data-driven prognostic model for staging of colorectal cancer

BACKGROUND

The aim of this study was to develop a novel prognostic model that captures complex interplay among clinical and histologic factors to predict survival of patients with colorectal cancer after a radical potentially curative resection.

STUDY DESIGN

Survival data of 2,505 colon cancer and 2,430 rectal cancer patients undergoing radical colorectal resection between 1969 and 2007 were analyzed by random forest technology. The effect of TNM and non-TNM factors such as histologic grade, lymph node ratio (number positive/number resected), type of operation, neoadjuvant and adjuvant treatment, American Society of Anesthesiologists (ASA) class, and age in staging and prognosis were evaluated. A forest of 1,000 random survival trees was grown using log-rank splitting. Competing risk-adjusted random survival forest methods were used to maximize survival prediction and produce importance measures of the predictor variables.

RESULTS

Competing risk-adjusted 5-year survival after resection of colon and rectal cancer was dominated by pT stage (ie, tumor infiltration depth) and lymph node ratio. Increased lymph node ratio was associated with worse survival within the same pT stage for both colon and rectal cancer patients. Whereas survival for colon cancer was affected by ASA grade, the type of resection and neoadjuvant therapy had a strong effect on rectal cancer survival. A similar pattern in predicted survival rates was observed for patients with fewer than 12 lymph nodes examined. Our model suggests that lymph node ratio remains a significant predictor of survival in this group.

CONCLUSIONS

A novel data-driven methodology predicts the survival times of patients with colorectal cancer and identifies patterns of cancer characteristics. The methods lead to stage groupings that could redefine the composition of TNM in a simple and orderly way. The higher predictive power of lymph node ratio as compared with traditional pN lymph node stage has specific implications and may address the important question of accuracy of staging in patients when fewer than 12 nodes are identified in the resection specimen.