Title: Construction and validation of a nomogram for cancer specific survival of postoperative
pancreatic cancer based on the SEER and China database
Version: 1 Date: 03 Jan 2024
Reviewer's report:
In this study "Construction and validation of a nomogram for cancer specific survival of
postoperative pancreatic cancer Based on SEER and China database." the authors aimed to
construct a nomogram that predicts postoperative cancer-specific survival of pancreatic cancer
patients. The objective here is clear. However, there are some limitations,
Although the authors list factor M and chemotherapy as variables in the nomogram, it is common
knowledge that these are very poor predictors of prognosis. Furthermore, in cases that did not
receive chemotherapy, patients are often too ill to intervene even if they wanted to. Thus, even
if the prognosis of these cases turns out to be poor, no strategy can be formulated. In other
words, the nomogram is expected to be completely useless clinically. It is unclear under what
circumstances the authors intend to use this model.
In order to create such a predictive model, one must fully consider the clinical context and
whether it is relevant to the actual clinical question. To give an example, "Which elderly patients
need surgical treatment?" would be very attractive and useful for clinical decision-making.
External validation in the Chiniese cohort is very important, but the very small number of cases
may overestimate the predictive power of the model.
Title: Construction and validation of a nomogram for cancer specific survival of postoperative
pancreatic cancer based on the SEER and China database
Version: 1 Date: 03 Jan 2024
Reviewer's report:
In this study "Construction and validation of a nomogram for cancer specific survival of
postoperative pancreatic cancer Based on SEER and China database." the authors aimed to
construct a nomogram that predicts postoperative cancer-specific survival of pancreatic cancer
patients. The objective here is clear. However, there are some limitations,
Although the authors list factor M and chemotherapy as variables in the nomogram, it is common
knowledge that these are very poor predictors of prognosis. Furthermore, in cases that did not
receive chemotherapy, patients are often too ill to intervene even if they wanted to. Thus, even
if the prognosis of these cases turns out to be poor, no strategy can be formulated. In other
words, the nomogram is expected to be completely useless clinically. It is unclear under what
circumstances the authors intend to use this model.
In order to create such a predictive model, one must fully consider the clinical context and
whether it is relevant to the actual clinical question. To give an example, "Which elderly patients
need surgical treatment?" would be very attractive and useful for clinical decision-making.
External validation in the Chiniese cohort is very important, but the very small number of cases
may overestimate the predictive power of the model.
Please review this paper.
user
Title: Construction and validation of a nomogram for cancer specific survival of postoperative
pancreatic cancer based on the SEER and China database
Version: 1 Date: 03 Jan 2024
Reviewer's report:
In this study "Construction and validation of a nomogram for cancer specific survival of
postoperative pancreatic cancer Based on SEER and China database." the authors aimed to
construct a nomogram that predicts postoperative cancer-specific survival of pancreatic cancer
patients. The objective here is clear. However, there are some limitations,
Although the authors list factor M and chemotherapy as variables in the nomogram, it is common
knowledge that these are very poor predictors of prognosis. Furthermore, in cases that did not
receive chemotherapy, patients are often too ill to intervene even if they wanted to. Thus, even
if the prognosis of these cases turns out to be poor, no strategy can be formulated. In other
words, the nomogram is expected to be completely useless clinically. It is unclear under what
circumstances the authors intend to use this model.
In order to create such a predictive model, one must fully consider the clinical context and
whether it is relevant to the actual clinical question. To give an example, "Which elderly patients
need surgical treatment?" would be very attractive and useful for clinical decision-making.
External validation in the Chiniese cohort is very important, but the very small number of cases
may overestimate the predictive power of the model.
assistant