Integration of IRK in the screening protocol

Oct 13, 2025 by miodeya.com 0 views

The Accuracy of the Risk Index of Malignancy-1 in Distinguishing Benign and Malignant Ovarian Tumors Before Surgery at RSUP. H. Adam Malik - RSUD. Dr. Pirngadi Medan

Introduction

Ovarian cancer is a type of cancer that affects the ovaries, and it is one of the leading causes of death among gynecological cancers. The early detection of ovarian cancer is crucial in determining the effectiveness of treatment and improving patient outcomes. Risk Index of Malignancy-1 (IRK) is a diagnostic tool that has been used to distinguish between benign and malignant ovarian tumors. However, its accuracy in distinguishing between these two types of tumors before surgery is still a topic of debate. This study aims to evaluate the effectiveness of IRK in distinguishing between benign and malignant ovarian tumors before surgical measures at RSUP. H. Adam Malik - RSUD. Dr. Pirngadi Medan.

Methodology

This study used a prospective diagnostic test analysis conducted during the period June 2010 to November 2010. A total of 37 patient samples were taken, consisting of 23 patients with benign tumors and 14 patients with malignant tumors. The age range of patients with ovarian cancer varied from 19 to 77 years old. The demographic analysis showed that the highest proportion of malignant ovarian tumors was found in the age group 40-64 years, with a total of 9 people (64.4%). Meanwhile, the age group under 20 years and over 65 years each had only one patient (7.1%). Of the 14 patients with malignant tumors, 4 of them (28.6%) had experienced menopause.

Results

The analysis showed that Ca 125> 35 U/ml levels had a sensitivity of 92.9%, 34.8% specificity, positive prediction value of 46.4%, and negative predictions of 88.9%. Meanwhile, ultrasonographic scores with U> 1 value showed sensitivity of 64.3%, specificity of 73.9%, positive prediction value 60%, and negative prediction value 77.3%. On the other hand, the risk index of malignancy with a cut-off value of more than 200 indicated sensitivity of 78.6%, specificity of 91.3%, positive prediction values of 84.6%, and negative prediction values of 87.5%. IRK accuracy in this study was recorded at 86.5%, with the optimal IRK cut-off value at 275.

Discussion

Based on these results, it can be concluded that the level of accuracy of IRK is much higher than Ca 125 levels and ultrasonographic scores. IRK shows excellence in terms of sensitivity and specificity, making it the right method for initial screening in distinguishing benign and malignant ovarian tumors before surgery. Thus, IRK can be a relevant reference criterion for patients with alleged malignant ovarian tumors to be referred to the oncology gynecology sub-section.

Additional Analysis

The accuracy of the risk index of malignancy (IRK) is very important in the context of the initial diagnosis of ovarian cancer, considering that ovarian cancer is often diagnosed in advanced stages. In clinical practice, methods that can provide fast and accurate results are needed to accelerate the necessary medical actions. This finding emphasizes the need for integration of IRK in the screening protocol to detect malignant ovarian tumors earlier, so that the right treatment can be given immediately.

Conclusion

This study contributes to the development of ovarian cancer diagnosis methods and opens opportunities for further research to explore other factors that may affect the accuracy of the diagnosis and management of patients with ovarian tumors. It is recommended that medical personnel involved in handling cases of ovarian tumors increases understanding of IRK use and combining them with other supporting examinations such as ultrasonography and CA 125 tests. Collaboration between these methods can improve the accuracy of diagnosis while providing a more clear picture to patients about their health conditions.

Recommendations

Integration of IRK in the screening protocol: IRK should be integrated into the screening protocol to detect malignant ovarian tumors earlier, so that the right treatment can be given immediately.
Increased understanding of IRK use: Medical personnel involved in handling cases of ovarian tumors should increase their understanding of IRK use and combining them with other supporting examinations such as ultrasonography and CA 125 tests.
Collaboration between methods: Collaboration between IRK, ultrasonography, and CA 125 tests can improve the accuracy of diagnosis while providing a more clear picture to patients about their health conditions.
Further research: Further research is needed to explore other factors that may affect the accuracy of the diagnosis and management of patients with ovarian tumors.

Limitations

This study has several limitations, including:

Small sample size: The sample size of this study was relatively small, which may limit the generalizability of the results.
Limited demographic analysis: The demographic analysis of this study was limited, which may not provide a comprehensive understanding of the population being studied.
Limited follow-up: The follow-up period of this study was limited, which may not provide a complete picture of the long-term outcomes of patients with ovarian tumors.

Future Directions

This study provides a foundation for further research on the accuracy of IRK in distinguishing between benign and malignant ovarian tumors. Future studies should aim to:

Increase the sample size: Future studies should aim to increase the sample size to provide a more comprehensive understanding of the population being studied.
Conduct a more comprehensive demographic analysis: Future studies should conduct a more comprehensive demographic analysis to provide a better understanding of the population being studied.
Conduct a longer follow-up period: Future studies should conduct a longer follow-up period to provide a complete picture of the long-term outcomes of patients with ovarian tumors.
Frequently Asked Questions (FAQs) about the Accuracy of the Risk Index of Malignancy-1 in Distinguishing Benign and Malignant Ovarian Tumors

Q: What is the Risk Index of Malignancy-1 (IRK)?

A: IRK is a diagnostic tool used to distinguish between benign and malignant ovarian tumors. It is a mathematical formula that takes into account various factors, including patient age, tumor size, and other clinical characteristics.

Q: How does IRK work?

A: IRK uses a combination of clinical and laboratory data to calculate a risk score for each patient. The risk score is then used to determine the likelihood of a patient having a malignant ovarian tumor.

Q: What are the benefits of using IRK?

A: IRK has several benefits, including:

Improved accuracy in distinguishing between benign and malignant ovarian tumors
Reduced need for unnecessary surgeries
Improved patient outcomes due to earlier detection and treatment of malignant tumors

Q: What are the limitations of IRK?

A: IRK has several limitations, including:

Limited availability of data on patient demographics and clinical characteristics
Limited understanding of the underlying biology of ovarian cancer
Potential for errors in data entry or calculation of risk scores

Q: How accurate is IRK in distinguishing between benign and malignant ovarian tumors?

A: The accuracy of IRK in distinguishing between benign and malignant ovarian tumors has been shown to be high in several studies, with sensitivity and specificity rates ranging from 70% to 90%.

Q: Can IRK be used in conjunction with other diagnostic tools?

A: Yes, IRK can be used in conjunction with other diagnostic tools, such as ultrasonography and CA 125 tests, to improve the accuracy of diagnosis and treatment of ovarian cancer.

Q: What are the potential risks of using IRK?

A: The potential risks of using IRK include:

False positive results, which can lead to unnecessary surgeries and treatment
False negative results, which can lead to delayed diagnosis and treatment of malignant tumors
Errors in data entry or calculation of risk scores, which can lead to inaccurate results

Q: How can IRK be used in clinical practice?

A: IRK can be used in clinical practice as a tool to aid in the diagnosis and treatment of ovarian cancer. It can be used in conjunction with other diagnostic tools and clinical judgment to determine the best course of treatment for each patient.

Q: What are the future directions for research on IRK?

A: Future research on IRK should focus on:

Improving the accuracy and reliability of IRK
Developing new and more effective diagnostic tools for ovarian cancer
Understanding the underlying biology of ovarian cancer and how it relates to IRK

Q: How can patients and healthcare providers get more information about IRK?

A: Patients and healthcare providers can get more information about IRK by:

Consulting with a healthcare provider or oncologist
Reviewing scientific literature and studies on IRK
Visiting the website of the American Cancer Society or other reputable health organizations for information on ovarian cancer and IRK.

Q: What are the implications of this study for patients with ovarian cancer?

A: This study has several implications for patients with ovarian cancer, including:

Improved accuracy in diagnosis and treatment of ovarian cancer
Reduced need for unnecessary surgeries and treatment
Improved patient outcomes due to earlier detection and treatment of malignant tumors.

Q: What are the implications of this study for healthcare providers?

A: This study has several implications for healthcare providers, including:

Improved accuracy in diagnosis and treatment of ovarian cancer
Reduced need for unnecessary surgeries and treatment
Improved patient outcomes due to earlier detection and treatment of malignant tumors.

Q: What are the implications of this study for the development of new diagnostic tools for ovarian cancer?

A: This study has several implications for the development of new diagnostic tools for ovarian cancer, including:

Improved accuracy and reliability of new diagnostic tools
Development of new and more effective diagnostic tools for ovarian cancer
Understanding the underlying biology of ovarian cancer and how it relates to new diagnostic tools.