Dear Editor,
In October–December 2024 issue of the Journal of Medical Physics, Adhab et al.[1] studied the serum levels of Zinc (Zn) and Copper (Cu) among Iraqi women with malignant and benign ovarian and uterine tumors. They found that lower serum Zn levels with increasing serum Cu levels might be linked directly to a greater risk of malignant uterine tumors while lower serum Cu levels with increasing serum Zn levels might be linked causally to a greater incidence of patients with malignant ovarian tumors. Moreover, these trace elements could differentiate between malignant and benign ovarian and uterine tumors. Despite the promising study results, we believe that the following limitation might impede the implementation of the study findings in research and clinical setups. The receiver operating characteristic (ROC) analysis is a high-powered instrument for evaluating the accomplishment of a given index test to diagnose a particular condition or disease. The area under ROC (AUROC) value is a summarized metric of the ROC curve which discloses the test’s capability to differentiate between nondiseased and diseased individuals. The ROC analysis could additionally be employed to define the optimal cutoff (COV) value, a value that maximizes an index test’s specificity and sensitivity. To soundly use the trace elements of Zn and Cu in differentiating malignant and benign tumors of the uterus and ovaries, predicting the progression of one tumor nature to another one, and institution of effective therapy, there is a necessity to refer to the predicted COV measured by plotting the ROC curve and calculating the AUROC.[2,3] Regretfully, Adhab et al.[1] made no attempt to plot the ROC and compute the AUROC for the trace elements under the study.
Conflicts of interest
There are no conflicts of interest.
Funding Statement
Nil.
REFERENCES
- 1.Adhab HG, Mahdi LH, Al-Hilo EM. Comparison of serum zinc and copper concentrations in females with ovarian and uterine tumors. J Med Phys. 2024;49:551–6. doi: 10.4103/jmp.jmp_126_24. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Çorbacıoğlu ŞK, Aksel G. Receiver operating characteristic curve analysis in diagnostic accuracy studies: A guide to interpreting the area under the curve value. Turk J Emerg Med. 2023;23:195–8. doi: 10.4103/tjem.tjem_182_23. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Chang PW, Newman TB. Receiver Operating Characteristic (ROC) curves: The basics and beyond. Hosp Pediatr. 2024;14:330–4. doi: 10.1542/hpeds.2023-007462. [DOI] [PubMed] [Google Scholar]
