Search Results
Search for other papers by Yang Lv in
Google Scholar
PubMed
Search for other papers by Ning Pu in
Google Scholar
PubMed
Search for other papers by Wei-lin Mao in
Google Scholar
PubMed
Search for other papers by Wen-qi Chen in
Google Scholar
PubMed
Search for other papers by Huan-yu Wang in
Google Scholar
PubMed
Search for other papers by Xu Han in
Google Scholar
PubMed
Search for other papers by Yuan Ji in
Google Scholar
PubMed
Search for other papers by Lei Zhang in
Google Scholar
PubMed
Search for other papers by Da-yong Jin in
Google Scholar
PubMed
Search for other papers by Wen-Hui Lou in
Google Scholar
PubMed
Search for other papers by Xue-feng Xu in
Google Scholar
PubMed
Aim
We aim to investigate the clinical characteristics of the rectal NECs and the prognosis-related factors and construct a nomogram for prognosis prediction.
Methods
The data of 41 patients and 1028 patients with rectal NEC were retrieved respectively from our institution and SEER database. OS or PFS was defined as the major study outcome. Variables were compared by chi-square test and t-test when appropriate. Kaplan–Meier analysis with log-rank test was used for survival analysis and the Cox regression analysis was applied. The nomogram integrating risk factors for predicting OS was constructed by R to achieve superior discriminatory ability. Predictive utility of the nomogram was determined by concordance index (C-index) and calibration curve.
Results
In the univariate and multivariate analyses, tumor differentiation, N stage, M stage and resection of primary site were identified as independent prognostic indicators. The linear regression relationship was found between the value of Ki-67 index and the duration of OS (P < 0.05). Furthermore, the independent prognostic factors were added to formulate prognostic nomogram. The constructed nomogram showed good performance according to the C-index.
Conclusions
Contrary to WHO classification guideline, we found that the rectal NEC diseases are heterogeneous and should be divided as different categories according to the pathological differentiation. Besides, the nomogram formulated in this study showed excellent discriminative capability to predict OS for those patients. More advanced predictive model for this disease is required to assist risk stratification via the formulated nomogram.
