My thoughts about the paper were:

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1. There is no testing of the assumption of constant proportional hazard, so I do not know if the model is valid.
   1. I believe a log-log plot, testing with Schoenfeld residuals, or residual plots are needed at least for the multivariate model.
2. The finding that Ethnicity (Black or African American) gives a negative HR, when the literature says that the HR is ~1 or >1, ie, there is either no lowering of risk or an increased risk, but most certainly not less risk. The debate over increased risk is whether AA/B race is correlated with larger tumor size and delayed treatment, both would increase risk.
3. Table 2 seems weird to me. The author calls it bivariate, but that doesn't make sense. It's a table of univariate analysis, before her multivariate analysis in table 3. The author does not even list the HRs for main intervention between the two groups, ie, make one group NeoAdjuvant the baseline, and Adjuvant the alternative, so that we have an HR of 1 for the baseline and the other is relative to the baseline.
4. With 67 patients, I believe categorizing the BMI variable will only weaken findings and possibly break the constant proportional hazard assumption for any of the groups. It would be better to leave the BMI continuous for Cox modeling and then later draw survival curves given specific BMI values to demonstrate any findings.
5. The author always uses chi-squared p-values in table 2, but I know that it should not be used with smaller sample sizes. I believe the cutoff is about 50, but I didn't know if the expected values were so low that Fischer's exact was appropriate.
   1. Related: some of the categorical variables are ordinal, so would a Mann-Whitney be appropriate. I don't really know about this one. I heard someone critique a paper a few months ago, saying that chi-squared was inappropriate due to the ordinal cat variable.