Nomograms to predict survival and the risk for developing local or distant recurrence in patients with rectal cancer treated with optional short-term radiotherapy

Gijn, W. van; Stiphout, Ruud G.P.M. van; Velde, C. J. H. van de; Valentini, Vincenzo; Lammering, Guido; Gambacorta, M.A.; Påhlman, Lars; Bujko, Krzysztof; Lambin, Philippe

doi:10.1093/annonc/mdv023

Cited by 50 publications

(52 citation statements)

References 28 publications

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“…Figure describes the search results. The scientific literature review and web‐based search identified 53 tools predicting survival in colon or rectal cancer, reported across 63 articles . Two articles reported on the development of two tools each .…”

Section: Resultsmentioning

confidence: 99%

Personalizing prognosis in colorectal cancer: A systematic review of the quality and nature of clinical prognostic tools for survival outcomes

Mahar

Compton

Halabi

et al. 2017

Journal of Surgical Oncology

113

104

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Integrating diverse types of prognostic information into accurate, individualized estimates of outcome in colorectal cancer is challenging. Significant heterogeneity in colorectal cancer prognostication tool quality exists. Methodology is incompletely or inadequately reported. Evaluations of the internal or external validity of the prognostic model are rarely performed. Prognostication tools are important devices for patient management, but tool reliability is compromised by poor quality. Guidance for future development of prognostication tools in colorectal cancer is needed.

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Section: Resultsmentioning

confidence: 99%

Personalizing prognosis in colorectal cancer: A systematic review of the quality and nature of clinical prognostic tools for survival outcomes

Mahar

Compton

Halabi

et al. 2017

Journal of Surgical Oncology

113

104

View full text Add to dashboard Cite

show abstract

“…Their study had a large sample size (2795 cases) with external validation, and the results were accurate and reliable. There are other models [39,40] for predicting survival and recurrence in patients with rectal cancer. Nevertheless, there are no such prediction models combining genetic information with clinical data.…”

Section: Discussionmentioning

confidence: 99%

INHBA is a prognostic predictor for patients with colon adenocarcinoma

Liang

et al. 2020

BMC Cancer

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Background: Colon adenocarcinoma (COAD) is one of the most lethal cancers. It is particularly important to accurately predict prognosis and to provide individualized treatment. Several lines of evidence suggest that genetic factors and clinicopathological characteristics are related to cancer onset and progression. The aim of this study was to identify potential prognostic genes and to develop a nomogram to predict survival and recurrence of COAD. Methods: To identify potential prognostic genes in COAD, microarray datasets were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were obtained from GEO2R. Venn diagram was drawn to select those genes that were overexpressed in all datasets, and survival analyses were performed to determine the prognostic values of the selected genes. New nomograms were developed based on the genes that were significantly associated with prognosis. Clinicopathological data were obtained from The Cancer Genome Atlas (TCGA). Finally, the new nomograms were compared head-to-head comparison with the TNM nomogram.Results: From GSE21510, GSE110223, GSE113513 and GSE110224, a total of 834, 218, 236 and 613 overexpressed DEGs were screened out, respectively. The Venn diagram revealed that 12 genes appeared in all four profiles. After survival analyses, only INHBA expression was associated with both overall survival (OS) and disease-free survival (DFS). Multivariate analyses revealed that age, pathological N and pathological M were significant independent risk factors for OS. Age, pathological N, pathological M and INHBA were significant independent risk factors for DFS. Two prediction models predicted the probability of 3-year survival and 5-year survival for OS and DFS, respectively. The concordance indexes were 0.785 for 3-year overall survival, 0.759 for 5-year overall survival, 0.789 for 3-year disease-free survival and 0.757 for 5-year disease-free survival. The head-to-head comparison according to timedependent ROC curves indicated that the new models had higher predictive accuracy. Decision curve analyses (DCA) indicated that the clinical value of the new models were higher than TNM models for predicting disease-free survival.Conclusion: The combination of INHBA expression with a clinical nomogram improves prognostic power in colon adenocarcinoma, especially for predicting recurrence.

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“…22 Most frequently evaluated prognostic factors include those directly associated to the neoplasm per se, that is, morphologic, proteomic, genomic or epigenomic, while the patient's immune and nutritional status have been often overlooked. [6][7][8][9] There is an increasing evidence that systemic inflammation plays a critical role in carcinogenesis and the invasion or metastatic processes in CRC. 30 The tumor-associated inflammatory response has been recognized to exert a contradictory effect, enhancing tumorigenesis and progression, and actually aiding incipient neoplasms to acquire hallmark capabilities.…”

Section: Discussionmentioning

confidence: 99%

“…[5][6][7] However, more refined tools are needed to further increase their prognostic value. The Memorial Sloan-Kettering Cancer Center model, which was designed to predict the 5-and 10-year disease-free survival after curative resection in patients with colon cancer, or the European CanCer Organisation/European Society of Surgical Oncology nomograms predicting recurrence, distant metastases and OS, 8,9 have been important contributions to the field. Nonetheless, the baseline immunonutritional status of patients was not considered as part of most of the conceptual models supporting these tools or were only defined in specific subpopulations of patients with CRC or specific stage groupings, 6 even when inflammation has been widely recognized as the promoter of multiple hallmark functional components of cancer.…”

Section: Introductionmentioning

confidence: 99%

Association of the prognostic nutritional index and overall survival in patients with colorectal cancer: A STROBE compliant retrospective cohort study

et al. 2019

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Background The TNM classification does not completely reflect the prognosis of patients with colorectal cancer (CRC). Several clinical factors have been used to increase its prognostic value, but factors pertaining to the patient's immunonutritional status have not usually been addressed. The aim of this study is to evaluate the role of Prognostic nutritional index (PNI) and other well‐known prognostic factors by multivariate analysis in a cohort of patients with CRC. Methods This is a retrospective cohort study of consecutive patients with CRC managed in a cancer center between January 1992 and December 2016. Cox's model was used to define the association of the PNI and other factors with Overall survival (OS). Results A total of 3301 patients were included: 47.7% were female and 52.3% were male, with a mean age of 58.7 years. By bivariate analysis, PNI was strongly associated with OS (Risk ratio [RR] 0.968, 95% Confidence interval [CI] 0.962‐0.974; P < 0.001). On multivariate analysis, PNI was an independent explanatory variable (as continuous variable and as categorized variable; RR 0.732, 95% CI 0.611‐0.878; RR 0.656, 95% CI 0.529‐0.813 and RR 0.646, 95% CI 0.521‐0.802, for quintiles 2, 3, and 4‐5, respectively); a biological gradient effect was demonstrated. The final prognostic model included PNI, location of the neoplasia in the colorectum, basal hemoglobin, lymphocyte count, neutrophil/lymphocyte ratio, platelet/lymphocyte ratio, TNM stage, differentiation degree, R classification, and postoperative complications. Conclusions PNI is a significant and independent prognostic factor in patients with CRC. Its prognostic value adds precision to the TNM staging system including specific subgroups of patients with CRC; it should be evaluated in prospective clinical studies.

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Nomograms to predict survival and the risk for developing local or distant recurrence in patients with rectal cancer treated with optional short-term radiotherapy

Cited by 50 publications

References 28 publications

Personalizing prognosis in colorectal cancer: A systematic review of the quality and nature of clinical prognostic tools for survival outcomes

Personalizing prognosis in colorectal cancer: A systematic review of the quality and nature of clinical prognostic tools for survival outcomes

INHBA is a prognostic predictor for patients with colon adenocarcinoma

Association of the prognostic nutritional index and overall survival in patients with colorectal cancer: A STROBE compliant retrospective cohort study

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