Contemporary Validation of a Nomogram Predicting Colon Cancer Recurrence, Revealing All-Stage Improved Outcomes

Clinical Calculator for Predicting Freedom From Recurrence After Resection of Stage I-III Colon Cancer in Patients With Microsatellite Instability

PURPOSE

Outcome for patients with nonmetastatic, microsatellite instability (MSI) colon cancer is favorable: however, high-risk cohorts exist. This study was aimed at developing and validating a nomogram model to predict freedom from recurrence (FFR) for patients with resected MSI colon cancer.

PATIENTS AND METHODS

Data from patients who underwent curative resection of stage I, II, or III MSI colon cancer in 2014-2021 (model training cohort, 384 patients, 33 events; median follow-up, 38.8 months) were retrospectively collected from institutional databases. Variables associated with recurrence in multivariable analysis were selected for inclusion in the clinical calculator. The calculator's predictive accuracy was measured with the concordance index and validated using data from patients who underwent treatment for MSI colon cancer in 2007-2013 (validation cohort, 164 patients, eight events; median follow-up, 84.8 months).

RESULTS

T category and number of positive lymph nodes were significantly associated with recurrence in multivariable analysis and were selected for inclusion in the clinical calculator. The calculator's concordance index for FFR in the model training cohort was 0.812 (95% CI, 0.742 to 0.873), compared with 0.759 (95% CI, 0.683 to 0.840) for the staging schema of the eighth edition of the American Joint Committee on Cancer Staging Manual. The concordance index for the validation cohort was 0.744 (95% CI, 0.666 to 0.822), confirming robust predictive accuracy.

CONCLUSION

Although in general patients with nonmetastatic MSI colon cancer had favorable outcome, patients with advanced T category and multiple metastatic lymph nodes had higher risk of recurrence. The clinical calculator identified patients with MSI colon cancer at high risk for recurrence, and this could inform surveillance strategies. In addition, the model could be used in trial design to identify patients suitable for novel adjuvant therapy.

Prognostic scoring system based on indicators reflecting the tumor glandular differentiation and microenvironment for patients with colorectal cancer

Prognostic stratification is an urgent concern for patients with colorectal cancer (CRC). The desmoplastic reaction (DR) is speculated to mirror the tumor microenvironment. DR types are considered independent prognostic indicators in CRC, but have not been incorporated in previous prognostic nomograms. We aimed to assess the prognostic significance of a novel approach incorporating histopathological indicators reflecting tumor glandular differentiation and microenvironment. We evaluated 329 consecutive patients with CRC who underwent surgical resection at Kansai Medical University. Histological glandular differentiation was scored as 2 (0 point), 3 (1 point), or 4 (2 points). Tumor buddings (TBs) were classified as TB1 (0 point), TB2 (1 point), or TB3 (2 points). pT1 or 2 was considered as 0 point, pT3 or 4 + DR non-immature type as 1 point, and pT3 or 4 + DR immature type as 2 points. Lymph node metastasis was classified as pN0 (0 point), pN1 (1 point), or pN2 (2 points). The preoperative carcinoembryonic antigen levels were categorized as < 5.0 ng/mL (0 point) and ≧5.0 (1 point). Considering these factors, the following D&M (tumor differentiation and microenvironment) scoring system was applied: I (0-2 points), II (3-4 points), III (5-6 points), and IV (7-9 points). Kaplan-Meier curves showed significant differences in disease-specific survival and recurrence-free survival among the assigned scores, highlighting their enhanced utility compared with the American Joint Committee on Cancer 8th edition staging system. The D&M scoring system was valuable as the initial prognostic nomogram, including DR.

Validation of a Clinical Calculator Predicting Freedom From Colon Cancer Recurrence After Surgery on the Basis of Molecular and Clinical Variables

BACKGROUND

The Memorial Sloan Kettering clinical calculator for estimating the likelihood of freedom from colon cancer recurrence on the basis of clinical and molecular variables was developed at a time when testing for microsatellite instability was performed selectively, based on patient age, family history, and histologic features. Microsatellite stability was assumed if no testing was done.

OBJECTIVE

This study aimed to validate the calculator in a cohort of patients who had all been tested for microsatellite instability.

DESIGN

Retrospective cohort analysis.

SETTINGS

Comprehensive cancer center.

PATIENTS

This study included consecutive patients who underwent curative resection for stage I, II, or III colon cancer between 2017 and 2019.

INTERVENTION

Universal testing of mircrosatellite phenotype in all cases.

MAIN OUTCOME MEASURES

The calculator's predictive accuracy was assessed using the concordance index and a calibration plot of predicted versus actual freedom from recurrence at 3 years after surgery. For a secondary sensitivity analysis, the presence of a tumor deposit(s) (disease category N1c) was considered equivalent to one positive lymph node (category N1a).

RESULTS

With a median follow-up of 32 months among survivors, the concordance index for the 745 patients in the cohort was 0.748 (95% CI, 0.693-0.801), and a plot of predicted versus observed recurrences approached the 45° diagonal, indicating good discrimination and calibration. In the secondary sensitivity analysis for tumor deposits, the concordance index was 0.755 (95% CI, 0.700-0.806).

LIMITATIONS

This study was limited by its retrospective, single-institution design.

CONCLUSIONS

These results, based on inclusion of actual rather than imputed microsatellite stability status and presence of tumor deposits, confirm the predictive accuracy and reliability of the calculator. See Video Abstract .

VALIDACIN DE UNA CALCULADORA CLNICA QUE PREDICE LA AUSENCIA DE RECURRENCIA POSTQUIRURGICA DEL CNCER DE COLON SOBRE LA BASE DE VARIABLES MOLECULARES Y CLNICAS

ANTECEDENTES:La calculadora clínica del Memorial Sloan Kettering para la estimación de la probabilidad de ausencia de recurrencia del cáncer de colon sobre la base de variables clínicas y moleculares, se desarrolló en un momento en que las pruebas para la inestabilidad de microsatélites se realizaban de forma selectiva, basadas en la edad del paciente, los antecedentes familiares y las características histológicas. Se asumía la estabilidad micro satelital si no se realizaba ninguna prueba.OBJETIVO:El objetivo de este estudio fue validar la calculadora en una cohorte de pacientes a los que se les había realizado la prueba de inestabilidad de microsatélites.DISEÑO:Análisis de cohorte retrospectivo.AJUSTE:Centro integral de cáncer.PACIENTES:Pacientes consecutivos con cáncer de colon que fueron sometidos a resección curativa por cáncer de colon en estadios I, II o III entre los años 2017 y 2019.PRINCIPALES MEDIDAS DE RESULTADO:La precisión predictiva de la calculadora fue evaluada mediante el índice de concordancia y un gráfico de calibración de la ausencia de recurrencia predecida versus la real a los 3 años tras la cirugía. A los efectos de un análisis secundario de sensibilidad, la presencia de depósito(s) tumoral(es) (categoría de enfermedad N1c) se consideró equivalente a un ganglio linfático positivo (categoría N1a).RESULTADOS:Con una mediana de seguimiento de 32 meses entre los supervivientes, el índice de concordancia para los 745 pacientes de la cohorte fue de 0,748 (intervalo de confianza del 95 %, 0,693 a 0,801), y una gráfica de recurrencias previstas versus observadas se acercó a la diagonal de 45°, indicando una buena discriminación y calibración. En el análisis secundario de sensibilidad para depósitos tumorales, el índice de concordancia fue de 0,755 (intervalo de confianza del 95 %, 0,700 a 0,806).LIMITACIONES:Diseño retrospectivo, institución única.CONCLUSIONES:Estos resultados, basados en la inclusión real del estado de estabilidad de microsatélites en lugar de imputado y la presencia de depósitos tumorales, confirman la precisión predictiva y la confiabilidad de la calculadora. (Traducción-Dr Osvaldo Gauto ).

Comparison of Robotic, Laparoscopic, and Open Resections of Nonmetastatic Colon Cancer

BACKGROUND

Laparoscopic resection for colon cancer has not been associated with improvements in oncological outcomes in comparison to open resection. Robotic resections are associated with increased lymph node yield and radicality of mesenteric resection in patients with right-sided tumors. It is unclear whether lymph node yield is higher in robotic resections in other parts of the colon and whether higher lymph node yield is associated with improved survival.

OBJECTIVE

To compare survival rates between robotic, laparoscopic, and open resections in a large cohort of patients with nonmetastatic colon cancer.

DESIGN

This is a retrospective observational study.

SETTING

A single comprehensive cancer center.

PATIENTS

Patients who underwent resection of nonmetastatic primary colon cancer between January 2006 and December 2018.

MAIN OUTCOME MEASURES

Univariable and multivariable models were used to identify predictors of disease-free and overall survival. Lymph node yield and perioperative outcomes were compared between operative approaches.

RESULTS

There were 2398 patients who met the inclusion criteria: 699 (29%) underwent open, 824 (34%) underwent laparoscopic, and 875 (36%) underwent robotic resection. The median follow-up was 3.8 years (45.4 months). Robotic surgery was associated with higher lymph node yield and radicality of mesenteric resection. On multivariable analysis, the surgical approach was not associated with a difference in disease-free or overall survival. Minimally invasive colectomy was associated with fewer complications and shorter length of stay in comparison to open surgery. In a direct comparison between the 2 minimally invasive approaches, robotic colectomy was associated with fewer complications, shorter length of stay, and lower conversion rate than laparoscopy.

LIMITATIONS

This was a single-center retrospective study.

CONCLUSIONS

Our data indicate that the 3 surgical approaches are similarly effective in treating primary resectable colon cancer and that differences in outcomes are observed primarily in the early postoperative period. See Video Abstract at http://links.lww.com/DCR/C115 .

COMPARACIN DE RESECCIONES ROBTICAS, LAPAROSCPICAS Y ABIERTAS DE CNCER DE COLON NO METASTSICO

ANTECEDENTES:La resección laparoscópica para el cáncer de colon no se ha asociado con mejoras en los resultados oncológicos en comparación con la resección abierta. Las resecciones robóticas se asocian con un mayor rendimiento de los ganglios linfáticos y la radicalidad de la resección mesentérica en pacientes con tumores del lado derecho. No está claro si la cosecha ganglionar es mayor en las resecciones robóticas en otras partes del colon y si un mayor rendimiento de los ganglios linfáticos se asocia con una mejor supervivencia.OBJETIVO:Comparar las tasas de supervivencia entre resecciones robóticas, laparoscópicas y abiertas en una gran cohorte de pacientes con cáncer de colon no metastásico.DISEÑO:Este es un estudio observacional retrospectivo.ESCENARIO:Este estudio se realizó en un único centro oncológico integral.PACIENTES:Pacientes que se sometieron a resección de cáncer de colon primario no metastásico entre enero de 2006 y diciembre de 2018.PRINCIPALES MEDIDAS DE RESULTADO:Se utilizaron modelos univariables y multivariables para identificar predictores de supervivencia libre de enfermedad y global. La cosecha ganglionar y los resultados perioperatorios se compararon entre los abordajes quirúrgicos.RESULTADOS:Hubo 2398 pacientes que cumplieron con los criterios de inclusión: 699 (29%) se sometieron a cirugía abierta, 824 (34%) se sometieron a resección laparoscópica y 875 (36%) se sometieron a resección robótica. La mediana de seguimiento fue de 3,8 años (45,4 meses). La cirugía robótica se asoció con una mayor cosecha ganglionar y la radicalidad de la resección mesentérica. En el análisis multivariable, el abordaje quirúrgico no se asoció con una diferencia en la supervivencia general o libre de enfermedad. La colectomía mínimamente invasiva se asoció con menos complicaciones y una estancia más corta en comparación con la cirugía abierta. En una comparación directa entre los dos enfoques mínimamente invasivos, la colectomía robótica se asoció con menos complicaciones, una estancia más corta y una tasa de conversión más baja que la laparoscopia.LIMITACIONES:Este fue un estudio retrospectivo de un solo centro.CONCLUSIONES:Nuestros datos indican que los tres enfoques quirúrgicos son igualmente efectivos en el tratamiento del cáncer de colon resecable primario y que las diferencias en los resultados se observan principalmente en el período posoperatorio temprano. Consulte Video Resumen en http://links.lww.com/DCR/C115 . (Traducción-Dr. Felipe Bellolio ).

Clinical Score to Predict Recurrence in Patients with Stage II and Stage III Colon Cancer

Background: The prognosis of patients with stage II and stage III colon cancer is heterogeneous. Clinical and pathological characteristics, such as tumor budding, may help to further refine the recurrence risk. Methods: We included all the patients with localized colon cancer at Hospital Universitario La Paz from October 2016 to October 2021. We built a prognostic score for recurrence in the training cohort based on multivariate cox regression analysis and categorized the patients into two risk groups. Results: A total of 440 patients were included in the training cohort. After a median follow-up of 45 months, 81 (18%) patients had a first tumor recurrence. T4, N2, and high tumor budding remained with a p value <0.05 at the last step of the multivariate cox regression model for time to recurrence (TTR). We assigned 2 points to T4 and 1 point to N2 and high tumor budding. Forty-five percent of the patients were assigned to the low-risk group (score = 0). Compared to the high-risk group (score 1−4), patients in the low-risk group had a significantly longer TTR (hazard ratio for disease recurrence of 0.14 (95%CI: 0.00 to 0.90; p < 0.045)). The results were confirmed in the validation cohort. Conclusions: In our study, we built a simple score to predict tumor recurrence based on T4, N2, and high tumor budding. Patients in the low-risk group, that comprised 44% of the cohort, had an excellent prognosis.

A Dynamic Clinical Calculator for Estimating Conditional Recurrence-Free Survival After Total Neoadjuvant Therapy for Rectal Cancer and Either Surgery or Watch-and-Wait Management

IMPORTANCE

The risk of recurrence in patients with locally advanced rectal cancer has historically been determined after surgery, relying on pathologic variables. A growing number of patients are being treated without surgery, and their risk of recurrence needs to be calculated differently.

OBJECTIVE

To develop a dynamic calculator for estimating the probability of recurrence-free survival (RFS) in patients with rectal cancer who undergo total neoadjuvant therapy (TNT) (induction systemic chemotherapy and chemoradiotherapy) and either surgery or watch-and-wait management.

DESIGN, SETTING, AND PARTICIPANTS

This cohort study included patients who presented with stage II or III rectal cancer between June 1, 2009, and March 1, 2015, at a comprehensive cancer center. Conditional modeling was incorporated into a previously validated clinical calculator to allow the probability of RFS to be updated based on whether the patient remained in watch-and-wait management or underwent delayed surgery. Data were analyzed from November 2021 to March 2022.

EXPOSURE

TNT followed by immediate surgery or watch-and-wait management with the possibility of delayed surgery.

MAIN OUTCOMES AND MEASURES

RFS, concordance index, calibration curves.

RESULTS

Of the 302 patients in the cohort, 204 (68%) underwent surgery within 3 months from TNT completion (median [range] age, 51 [22-82] years; 78 [38%] women), 54 (18%) underwent surgery more than 3 months from TNT completion (ie, delayed surgery; median [range] age, 62 [31-87] years; 30 [56%] female), and 44 (14%) remained in watch-and-wait management as of April 21, 2021 (median [range] age, 58 [32-89] years; 16 [36%] women). Among patients who initially opted for watch-and-wait management, migration to surgery due to regrowth or patient choice occurred mostly within the first year following completion of TNT, and RFS did not differ significantly whether surgery was performed 3.0 to 5.9 months (73%; 95% CI, 52%-92%) vs 6.0 to 11.9 months (71%; 95% CI, 51%-99%) vs more than 12.0 months (70%; 95% CI, 49%-100%) from TNT completion (P = .70). RFS for patients in the watch-and-wait cohort at 12 months from completion of TNT more closely resembled patients who had undergone surgery and had a pathologic complete response than the watch-and-wait cohort at 3 months from completion of TNT. Accordingly, model performance improved over time, and the concordance index increased from 0.62 (95% CI, 0.53-0.71) at 3 months after TNT to 0.66 (95% CI, 0-0.75) at 12 months.

CONCLUSIONS AND RELEVANCE

In this cohort study of patients with rectal cancer, the clinical calculator reliably estimated the likelihood of RFS for patients who underwent surgery immediately after TNT, patients who underwent delayed surgery after entering watch-and-wait management, and patients who remained in watch-and-wait management. Delayed surgery following attempted watch-and-wait did not appear to compromise oncologic outcomes. The risk calculator provided conditional survival estimates at any time during surveillance and could help physicians counsel patients with rectal cancer about the consequences of alternative treatment pathways and thereby support informed decisions that incorporate patients' preferences.

A Prediction Model for Tumor Recurrence in Stage II–III Colorectal Cancer Patients: From a Machine Learning Model to Genomic Profiling

Background: Colorectal cancer (CRC) is one of the most prevalent malignant diseases worldwide. Risk prediction for tumor recurrence is important for making effective treatment decisions and for the survival outcomes of patients with CRC after surgery. Herein, we aimed to explore a prediction algorithm and the risk factors for postoperative tumor recurrence using a machine learning (ML) approach with standardized pathology reports for patients with stage II and III CRC. Methods: Pertinent clinicopathological features were compiled from medical records and standardized pathology reports of patients with stage II and III CRC. Four ML models based on logistic regression (LR), random forest (RF), classification and regression decision trees (CARTs), and support vector machine (SVM) were applied for the development of the prediction algorithm. The area under the curve (AUC) of the ML models was determined in order to compare the prediction accuracy. Genomic studies were performed using a panel-targeted next-generation sequencing approach. Results: A total of 1073 patients who received curative intent surgery at the National Cheng Kung University Hospital between January 2004 and January 2019 were included. Based on conventional statistical methods, chemotherapy (p = 0.003), endophytic tumor configuration (p = 0.008), TNM stage III disease (p < 0.001), pT4 (p < 0.001), pN2 (p < 0.001), increased numbers of lymph node metastases (p < 0.001), higher lymph node ratios (LNR) (p < 0.001), lymphovascular invasion (p < 0.001), perineural invasion (p < 0.001), tumor budding (p = 0.004), and neoadjuvant chemoradiotherapy (p = 0.025) were found to be correlated with the tumor recurrence of patients with stage II–III CRC. While comparing the performance of different ML models for predicting cancer recurrence, the AUCs for LR, RF, CART, and SVM were found to be 0.678, 0.639, 0.593, and 0.581, respectively. The LR model had a better accuracy value of 0.87 and a specificity value of 1 in the testing set. Two prognostic factors, age and LNR, were selected by multivariable analysis and the four ML models. In terms of age, older patients received fewer cycles of chemotherapy and radiotherapy (p < 0.001). Right-sided colon tumors (p = 0.002), larger tumor sizes (p = 0.008) and tumor volumes (p = 0.049), TNM stage II disease (p < 0.001), and advanced pT3–4 stage diseases (p = 0.04) were found to be correlated with the older age of patients. However, pN2 diseases (p = 0.005), lymph node metastasis number (p = 0.001), LNR (p = 0.004), perineural invasion (p = 0.018), and overall survival rate (p < 0.001) were found to be decreased in older patients. Furthermore, PIK3CA and DNMT3A mutations (p = 0.032 and 0.039, respectively) were more frequently found in older patients with stage II–III CRC compared to their younger counterparts. Conclusions: This study demonstrated that ML models have a comparable predictive power for determining cancer recurrence in patients with stage II–III CRC after surgery. Advanced age and high LNR were significant risk factors for cancer recurrence, as determined by ML algorithms and multivariable analyses. Distinctive genomic profiles may contribute to discrete clinical behaviors and survival outcomes between patients of different age groups. Studies incorporating complete molecular and genomic profiles in cancer prediction models are beneficial for patients with stage II–III CRC.

Development and Validation of the Individualized Prognostic Nomograms in Patients With Right- and Left-Sided Colon Cancer

Background

The overall survival (OS) of patients diagnosed with colon cancer (CC) varied greatly, so did the patients with the same tumor stage. We aimed to design a nomogram that is capable of predicting OS in resected left-sided colon cancers (LSCC) and right-sided colon cancers (RSCC), and thus to stratify patients into different risk groups, respectively.

Methods

Records from a retrospective cohort of 577 patients with complete information were used to construct the nomogram. Univariate and multivariate analyses screened risk factors associated with overall survival. The performance of the nomogram was evaluated with concordance index (c-index), calibration plots, and decision curve analyses for discrimination, accuracy, calibration ability, and clinical net benefits, respectively, which was further compared with the American Joint Committee on Cancer (AJCC) 8th tumor-node-metastasis (TNM) classification. Risk stratification based on nomogram scores was performed with recursive partitioning analysis.

Results

The LSCC nomogram incorporated carbohydrate antigen 12-5 (CA12-5), age and log odds of positive lymph nodes (LODDS), and RSCC nomogram enrolled tumor stroma percentage (TSP), age and LODDS. Compared with the TNM classification, the LSCC and RSCC nomograms both had a statistically higher C-index (0.837, 95% CI: 0.827-0.846 and 0.780, 95% CI 0.773-0.787, respectively) and more clinical net benefits, respectively. Calibration plots revealed no deviations from reference lines. All results were reproducible in the validation cohort.

Conclusions

An original predictive nomogram was constructed and validated for OS in patients with CC after surgery, which had facilitated physicians to appraise the individual survival of postoperative patients accurately and to identify high-risk patients who were in need of more aggressive treatment and follow-up strategies.

Development and Assessment of a Clinical Calculator for Estimating the Likelihood of Recurrence and Survival Among Patients With Locally Advanced Rectal Cancer Treated With Chemotherapy, Radiotherapy, and Surgery

IMPORTANCE

Predicting outcomes in patients receiving neoadjuvant therapy for rectal cancer is challenging because of tumor downstaging. Validated clinical calculators that can estimate recurrence-free survival (RFS) and overall survival (OS) among patients with rectal cancer who have received multimodal therapy are needed.

OBJECTIVE

To develop and validate clinical calculators providing estimates of rectal cancer recurrence and survival that are better for individualized decision-making than the American Joint Committee on Cancer (AJCC) staging system or the neoadjuvant rectal (NAR) score.

DESIGN, SETTING, AND PARTICIPANTS

This prognostic study developed risk models, graphically represented as nomograms, for patients with incomplete pathological response using Cox proportional hazards and multivariable regression analyses with restricted cubic splines. Because patients with complete pathological response to neoadjuvant therapy had uniformly favorable outcomes, their predictions were obtained separately. The study included 1400 patients with stage II or III rectal cancer who received treatment with chemotherapy, radiotherapy, and surgery at 2 comprehensive cancer centers (Memorial Sloan Kettering [MSK] Cancer Center and Siteman Cancer Center [SCC]) between January 1, 1998, and December 31, 2017. Patients from the MSK cohort received chemoradiation, surgery, and adjuvant chemotherapy from January 1, 1998, to December 31, 2014; these patients were randomly assigned to either a model training group or an internal validation group. Models were externally validated using data from the SCC cohort, who received either chemoradiation, surgery, and adjuvant chemotherapy (chemoradiotherapy group) or short-course radiotherapy, consolidation chemotherapy, and surgery (total neoadjuvant therapy with short-course radiotherapy group) from January 1, 2009, to December 31, 2017. Data were analyzed from March 1, 2020, to January 10, 2021.

EXPOSURES

Chemotherapy, radiotherapy, chemoradiotherapy, and surgery.

MAIN OUTCOMES AND MEASURES

Recurrence-free survival and OS were the outcome measures, and the discriminatory performance of the clinical calculators was measured with concordance index and calibration plots. The ability of the clinical calculators to predict RFS and OS was compared with that of the AJCC staging system and the NAR score. The models for RFS and OS among patients with incomplete pathological response included postoperative pathological tumor category, number of positive lymph nodes, tumor distance from anal verge, and large- and small-vessel venous and perineural invasion; age was included in the risk model for OS. The final clinical calculators provided RFS and OS estimates derived from Kaplan-Meier curves for patients with complete pathological response and from risk models for patients with incomplete pathological response.

RESULTS

Among 1400 total patients with locally advanced rectal cancer, the median age was 57.8 years (range, 18.0-91.9 years), and 863 patients (61.6%) were male, with tumors at a median distance of 6.7 cm (range, 0-15.0 cm) from the anal verge. The MSK cohort comprised 1069 patients; of those, 710 were assigned to the model training group and 359 were assigned to the internal validation group. The SCC cohort comprised 331 patients; of those, 200 were assigned to the chemoradiotherapy group and 131 were assigned to the total neoadjuvant therapy with short-course radiotherapy group. The concordance indices in the MSK validation data set were 0.70 (95% CI, 0.65-0.76) for RFS and 0.73 (95% CI, 0.65-0.80) for OS. In the external SCC data set, the concordance indices in the chemoradiotherapy group were 0.71 (95% CI, 0.62-0.81) for RFS and 0.72 (95% CI, 0.59-0.85) for OS; the concordance indices in the total neoadjuvant therapy with short-course radiotherapy group were 0.62 (95% CI, 0.49-0.75) for RFS and 0.67 (95% CI, 0.46-0.84) for OS. Calibration plots confirmed good agreement between predicted and observed events. These results compared favorably with predictions based on the AJCC staging system (concordance indices for MSK validation: RFS = 0.69 [95% CI, 0.64-0.74]; OS = 0.67 [95% CI, 0.58-0.75]) and the NAR score (concordance indices for MSK validation: RFS = 0.56 [95% CI, 0.50-0.63]; OS = 0.56 [95% CI, 0.46-0.66]). Furthermore, the clinical calculators provided more individualized outcome estimates compared with the categorical schemas (eg, estimated RFS for patients with AJCC stage IIIB disease ranged from 7% to 68%).

CONCLUSIONS AND RELEVANCE

In this prognostic study, clinical calculators were developed and validated; these calculators provided more individualized estimates of the likelihood of RFS and OS than the AJCC staging system or the NAR score among patients with rectal cancer who received multimodal treatment. The calculators were easy to use and applicable to both short- and long-course radiotherapy regimens, and they may be used to inform surveillance strategies and facilitate future clinical trials and statistical power calculations.

Accurate population-based model for individual prediction of colon cancer recurrence

BACKGROUND

Prediction models are useful tools in the clinical management of colon cancer patients, particularly when estimating the recurrence rate and, thus, the need for adjuvant treatment. However, the most used models (MSKCC, ACCENT) are based on several decades-old patient series from clinical trials, likely overestimating the current risk of recurrence, especially in low-risk groups, as outcomes have improved over time. The aim was to develop and validate an updated model for the prediction of recurrence within 5 years after surgery using routinely collected clinicopathologic variables.

MATERIAL AND METHODS

A population-based cohort from the Swedish Colorectal Cancer Registry of 16,134 stage I-III colon cancer cases was used. A multivariable model was constructed using Cox proportional hazards regression. Three-quarters of the cases were used for model development and one quarter for internal validation. External validation was performed using 12,769 stage II-III patients from the Norwegian Colorectal Cancer Registry. The model was compared to previous nomograms.

RESULTS

The nomogram consisted of eight variables: sex, sidedness, pT-substages, number of positive and found lymph nodes, emergency surgery, lymphovascular and perineural invasion. The area under the curve (AUC) was 0.78 in the model, 0.76 in internal validation, and 0.70 in external validation. The model calibrated well, especially in low-risk patients, and performed better than existing nomograms in the Swedish registry data. The new nomogram's AUC was equal to that of the MSKCC but the calibration was better.

CONCLUSION

The nomogram based on recently operated patients from a population registry predicts recurrence risk more accurately than previous nomograms. It performs best in the low-risk groups where the risk-benefit ratio of adjuvant treatment is debatable and the need for an accurate prediction model is the largest.

Overall survival nomogram for patients with spinal bone metastases (SBM)

•Demographic features are essential for a more personalize survival prediction of spinal bone metastasis (SBM).•Women have a relatively better survival chance than men before 75 years, while men have better survival after this age.•SBM survival is not dependent on the number of spinal metastases.

Recurrence of Non-functional Pancreatic Neuroendocrine Tumors After Curative Resection: A Tumor Burden-Based Prediction Model

BACKGROUND

Patients can experience recurrence following curative-intent resection of non-functional pancreatic neuroendocrine tumors (NF-pNETs). We sought to develop a nomogram to risk stratify patients relative to recurrence following resection of NF-pNETs.

METHODS

Patients who underwent curative-intent resection for NF-pNETs between 1997 and 2016 were identified from a multi-institutional database. The impact of clinicopathologic factors, including tumor burden score (TBS) (TBS² = (maximum tumor diameter)² + (number of tumors)²), was assessed relative to recurrence-free survival (RFS), and a nomogram was developed and internally validated.

RESULTS

With a median follow-up of 31.0 months (IQR 11.3-56.6 months), 66 (15.8%) out of 416 patients in the cohort experienced tumor recurrence. Overall, 3-, 5-, and 10-year RFS following curative-intent resection was 83.2%, 74.0%, and 44.7%, respectively. Several factors were associated with risk of recurrence including tumor grade (referent G1: G2, HR 4.07, 95% CI 2.29-7.26, p < 0.001; G3, HR 10.83, 95% CI 3.72-31.53, p < 0.001), lymph node metastasis (LNM) (HR 4.71, 95% CI 2.69-8.26, p < 0.001), as well as TBS (referent low: medium, HR 4.36, 95% CI 2.06-9.24, p < 0.001; high, HR 6.04, 95% CI 2.96-12.31, p < 0.001). A weighted nomogram including tumor grade (G1 0, G2 54.19, G3 100), LNM (N0 0, N1 42.06), and TBS (low 0, medium 44.07, high 56.48) was developed. The discriminatory power of the nomogram was very good with a C-index of 0.75 (95% CI, 0.66-0.79) in the training cohort and 0.71 (95% CI, 0.65-0.75) in the validation cohort. In addition, the nomogram performed better than the current 8th edition of AJCC TNM staging system, which had a C-index of 0.67 (95% CI, 0.60-0.73).

CONCLUSIONS

A nomogram that incorporated tumor grade, LNM, and TBS was established that had good discrimination and calibration. The nomogram may be an effective tool to stratify patients relative to recurrence risk following resection of NF-pNETs.

Clinical Calculator Based on Molecular and Clinicopathologic Characteristics Predicts Recurrence Following Resection of Stage I-III Colon Cancer

PURPOSE

Clinical calculators and nomograms have been endorsed by the American Joint Committee on Cancer (AJCC), as they provide the most individualized and accurate estimate of patient outcome. Using molecular and clinicopathologic variables, a third-generation clinical calculator was built to predict recurrence following resection of stage I-III colon cancer.

METHODS

Prospectively collected data from 1,095 patients who underwent colectomy between 2007 and 2014 at Memorial Sloan Kettering Cancer Center were used to develop a clinical calculator. Discrimination was measured with concordance index, and variability in individual predictions was assessed with calibration curves. The clinical calculator was externally validated with a patient cohort from Washington University's Siteman Cancer Center in St Louis.

RESULTS

The clinical calculator incorporated six variables: microsatellite genomic phenotype; AJCC T category; number of tumor-involved lymph nodes; presence of high-risk pathologic features such as venous, lymphatic, or perineural invasion; presence of tumor-infiltrating lymphocytes; and use of adjuvant chemotherapy. The concordance index was 0.792 (95% CI, 0.749 to 0.837) for the clinical calculator, compared with 0.708 (95% CI, 0.671 to 0.745) and 0.757 (0.715 to 0.799) for the staging schemes of the AJCC manual's 5th and 8th editions, respectively. External validation confirmed robust performance, with a concordance index of 0.738 (95% CI, 0.703 to 0.811) and calibration plots of predicted probability and observed events approaching a 45° diagonal.

CONCLUSION

This third-generation clinical calculator for predicting cancer recurrence following curative colectomy successfully incorporates microsatellite genomic phenotype and the presence of tumor-infiltrating lymphocytes, resulting in improved discrimination and predictive accuracy. This exemplifies an evolution of a clinical calculator to maintain relevance by incorporating emerging variables as they become validated and accepted in the oncologic community.

Recurrence Risk after Radical Colorectal Cancer Surgery-Less Than before, But How High Is It?

Simple Summary

Evidence indicates that recurrence risk after colon cancer today is less than it was when trials performed decades ago showed that adjuvant chemotherapy reduces the risk and prolong disease-free and overall survival. After rectal cancer surgery, local recurrence rates have decreased but it is unclear if systemic recurrences have. After a systematic review of available literature reporting recurrence risks after curative colorectal cancer surgery we report that the risks are lower today than they were in the past and that this risk reduction is not solely ascribed to the use of adjuvant therapy. Adjuvant therapy always means overtreatment of many patients, already cured by the surgery. Fewer recurrences mean that progress in the care of these patients has happened but also that the present guidelines giving recommendations based upon old data must be adjusted. The relative gains from adding chemotherapy are not altered, but the absolute number of patients gaining is less.

Abstract

Adjuvant chemotherapy aims at eradicating tumour cells sometimes present after radical surgery for a colorectal cancer (CRC) and thereby diminish the recurrence rate and prolong time to recurrence (TTR). Remaining tumour cells will lead to recurrent disease that is usually fatal. Adjuvant therapy is administered based upon the estimated recurrence risk, which in turn defines the need for this treatment. This systematic overview aims at describing whether the need has decreased since trials showing that adjuvant chemotherapy provides benefits in colon cancer were performed decades ago. Thanks to other improvements than the administration of adjuvant chemotherapy, such as better staging, improved surgery, the use of radiotherapy and more careful pathology, recurrence risks have decreased. Methodological difficulties including intertrial comparisons decades apart and the present selective use of adjuvant therapy prevent an accurate estimate of the magnitude of the decreased need. Furthermore, most trials do not report recurrence rates or TTR, only disease-free and overall survival (DFS/OS). Fewer colon cancer patients, particularly in stage II but also in stage III, today display a sufficient need for adjuvant treatment considering the burden of treatment, especially when oxaliplatin is added. In rectal cancer, neo-adjuvant treatment will be increasingly used, diminishing the need for adjuvant treatment.

Nomogram for pneumonia prediction among children and young people with cerebral palsy: A population-based cohort study

BACKGROUND

Pneumonia is the leading cause of death among children and young people (CYP) with severe cerebral palsy (CP). Only a few studies used nomogram for assessing risk factors and the probability of pneumonia. Therefore, we aimed to identify risk factors and devise a nomogram for identifying the probability of severe pneumonia in CYP with severe CP.

METHODS

This retrospective nationwide population-based cohort study examined CYP with newly diagnosed severe CP before 18 years old between January 1st, 1997 and December 31st, 2013 and followed them up through December 31st, 2013. The primary endpoint was defined as the occurrence of severe pneumonia with ≥ 5 days of hospitalization. Logistic regression analysis was used for determining demographic factors and comorbidities associated with severe pneumonia. These factors were assigned integer points to create a scoring system to identify children at high risk for severe pneumonia.

RESULTS

Among 6,356 CYP with newly diagnosed severe CP, 2,135 (33.59%) had severe pneumonia. Multivariable logistic regression analysis revealed that seven independent predictive factors, namely age <3 years, male sex, and comorbidities of pressure ulcer, gastroesophageal reflux, asthma, seizures, and perinatal complications. A nomogram was devised by employing these seven significant predictive factors. The prediction model presented favorable discrimination performance.

CONCLUSIONS

The nomogram revealed that age, male sex, history of pressure ulcer, gastroesophageal reflux, asthma, seizures, and perinatal complications were potential risk factors for severe pneumonia among CYP with severe CP.