Journal of Clinical and Diagnostic Research, ISSN - 0973 - 709X

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On Sep 2018




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On Sep 2018




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"Journal of Clinical and Diagnostic Research is at present a well-known Indian originated scientific journal which started with a humble beginning. I have been associated with this journal since many years. I appreciate the Editor, Dr. Hemant Jain, for his constant effort in bringing up this journal to the present status right from the scratch. The journal is multidisciplinary. It encourages in publishing the scientific articles from postgraduates and also the beginners who start their career. At the same time the journal also caters for the high quality articles from specialty and super-specialty researchers. Hence it provides a platform for the scientist and researchers to publish. The other aspect of it is, the readers get the information regarding the most recent developments in science which can be used for teaching, research, treating patients and to some extent take preventive measures against certain diseases. The journal is contributing immensely to the society at national and international level."



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Lucknow
On Sep 2018




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Calcutta National Medical College & Hospital , Kolkata




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Muzaffarnagar Medical College,
Muzaffarnagar.
On Aug 2018




Dr. Arundhathi. S
"Journal of Clinical and Diagnostic Research (JCDR) is a reputed peer reviewed journal and is constantly involved in publishing high quality research articles related to medicine. Its been a great pleasure to be associated with this esteemed journal as a reviewer and as an author for a couple of years. The editorial board consists of many dedicated and reputed experts as its members and they are doing an appreciable work in guiding budding researchers. JCDR is doing a commendable job in scientific research by promoting excellent quality research & review articles and case reports & series. The reviewers provide appropriate suggestions that improve the quality of articles. I strongly recommend my fraternity to encourage JCDR by contributing their valuable research work in this widely accepted, user friendly journal. I hope my collaboration with JCDR will continue for a long time".



Dr. Arundhathi. S
MBBS, MD (Pathology),
Sanjay Gandhi institute of trauma and orthopedics,
Bengaluru.
On Aug 2018




Dr. Mamta Gupta,
"It gives me great pleasure to be associated with JCDR, since last 2-3 years. Since then I have authored, co-authored and reviewed about 25 articles in JCDR. I thank JCDR for giving me an opportunity to improve my own skills as an author and a reviewer.
It 's a multispecialty journal, publishing high quality articles. It gives a platform to the authors to publish their research work which can be available for everyone across the globe to read. The best thing about JCDR is that the full articles of all medical specialties are available as pdf/html for reading free of cost or without institutional subscription, which is not there for other journals. For those who have problem in writing manuscript or do statistical work, JCDR comes for their rescue.
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Reviewing articles is no less a pain staking process and requires in depth perception, knowledge about the topic for review. It requires time and concentration, yet I enjoy doing it. The JCDR website especially for the reviewers is quite user friendly. My suggestions for improving the journal is, more strict review process, so that only high quality articles are published. I find a a good number of articles in Obst. Gynae, hence, a new journal for this specialty titled JCDR-OG can be started. May be a bimonthly or quarterly publication to begin with. Only selected articles should find a place in it.
An yearly reward for the best article authored can also incentivize the authors. Though the process of finding the best article will be not be very easy. I do not know how reviewing process can be improved. If an article is being reviewed by two reviewers, then opinion of one can be communicated to the other or the final opinion of the editor can be communicated to the reviewer if requested for. This will help one’s reviewing skills.
My best wishes to Dr. Hemant Jain and all the editorial staff of JCDR for their untiring efforts to bring out this journal. I strongly recommend medical fraternity to publish their valuable research work in this esteemed journal, JCDR".



Dr. Mamta Gupta
Consultant
(Ex HOD Obs &Gynae, Hindu Rao Hospital and associated NDMC Medical College, Delhi)
Aug 2018




Dr. Rajendra Kumar Ghritlaharey

"I wish to thank Dr. Hemant Jain, Editor-in-Chief Journal of Clinical and Diagnostic Research (JCDR), for asking me to write up few words.
Writing is the representation of language in a textual medium i e; into the words and sentences on paper. Quality medical manuscript writing in particular, demands not only a high-quality research, but also requires accurate and concise communication of findings and conclusions, with adherence to particular journal guidelines. In medical field whether working in teaching, private, or in corporate institution, everyone wants to excel in his / her own field and get recognised by making manuscripts publication.


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Salient features of the JCDR: It is a biomedical, multidisciplinary (including all medical and dental specialities), e-journal, with wide scope and extensive author support. At the same time, a free text of manuscript is available in HTML and PDF format. There is fast growing authorship and readership with JCDR as this can be judged by the number of articles published in it i e; in Feb 2007 of its first issue, it contained 5 articles only, and now in its recent volume published in April 2011, it contained 67 manuscripts. This e-journal is fulfilling the commitments and objectives sincerely, (as stated by Editor-in-chief in his preface to first edition) i e; to encourage physicians through the internet, especially from the developing countries who witness a spectrum of disease and acquire a wealth of knowledge to publish their experiences to benefit the medical community in patients care. I also feel that many of us have work of substance, newer ideas, adequate clinical materials but poor in medical writing and hesitation to submit the work and need help. JCDR provides authors help in this regards.
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Every one of us: authors, reviewers, editors, and publisher are responsible for enhancing the stature of the journal. I wish for a great success for JCDR."



Thanking you
With sincere regards
Dr. Rajendra Kumar Ghritlaharey, M.S., M. Ch., FAIS
Associate Professor,
Department of Paediatric Surgery, Gandhi Medical College & Associated
Kamla Nehru & Hamidia Hospitals Bhopal, Madhya Pradesh 462 001 (India)
E-mail: drrajendrak1@rediffmail.com
On May 11,2011




Dr. Shankar P.R.

"On looking back through my Gmail archives after being requested by the journal to write a short editorial about my experiences of publishing with the Journal of Clinical and Diagnostic Research (JCDR), I came across an e-mail from Dr. Hemant Jain, Editor, in March 2007, which introduced the new electronic journal. The main features of the journal which were outlined in the e-mail were extensive author support, cash rewards, the peer review process, and other salient features of the journal.
Over a span of over four years, we (I and my colleagues) have published around 25 articles in the journal. In this editorial, I plan to briefly discuss my experiences of publishing with JCDR and the strengths of the journal and to finally address the areas for improvement.
My experiences of publishing with JCDR: Overall, my experiences of publishing withJCDR have been positive. The best point about the journal is that it responds to queries from the author. This may seem to be simple and not too much to ask for, but unfortunately, many journals in the subcontinent and from many developing countries do not respond or they respond with a long delay to the queries from the authors 1. The reasons could be many, including lack of optimal secretarial and other support. Another problem with many journals is the slowness of the review process. Editorial processing and peer review can take anywhere between a year to two years with some journals. Also, some journals do not keep the contributors informed about the progress of the review process. Due to the long review process, the articles can lose their relevance and topicality. A major benefit with JCDR is the timeliness and promptness of its response. In Dr Jain's e-mail which was sent to me in 2007, before the introduction of the Pre-publishing system, he had stated that he had received my submission and that he would get back to me within seven days and he did!
Most of the manuscripts are published within 3 to 4 months of their submission if they are found to be suitable after the review process. JCDR is published bimonthly and the accepted articles were usually published in the next issue. Recently, due to the increased volume of the submissions, the review process has become slower and it ?? Section can take from 4 to 6 months for the articles to be reviewed. The journal has an extensive author support system and it has recently introduced a paid expedited review process. The journal also mentions the average time for processing the manuscript under different submission systems - regular submission and expedited review.
Strengths of the journal: The journal has an online first facility in which the accepted manuscripts may be published on the website before being included in a regular issue of the journal. This cuts down the time between their acceptance and the publication. The journal is indexed in many databases, though not in PubMed. The editorial board should now take steps to index the journal in PubMed. The journal has a system of notifying readers through e-mail when a new issue is released. Also, the articles are available in both the HTML and the PDF formats. I especially like the new and colorful page format of the journal. Also, the access statistics of the articles are available. The prepublication and the manuscript tracking system are also helpful for the authors.
Areas for improvement: In certain cases, I felt that the peer review process of the manuscripts was not up to international standards and that it should be strengthened. Also, the number of manuscripts in an issue is high and it may be difficult for readers to go through all of them. The journal can consider tightening of the peer review process and increasing the quality standards for the acceptance of the manuscripts. I faced occasional problems with the online manuscript submission (Pre-publishing) system, which have to be addressed.
Overall, the publishing process with JCDR has been smooth, quick and relatively hassle free and I can recommend other authors to consider the journal as an outlet for their work."



Dr. P. Ravi Shankar
KIST Medical College, P.O. Box 14142, Kathmandu, Nepal.
E-mail: ravi.dr.shankar@gmail.com
On April 2011
Anuradha

Dear team JCDR, I would like to thank you for the very professional and polite service provided by everyone at JCDR. While i have been in the field of writing and editing for sometime, this has been my first attempt in publishing a scientific paper.Thank you for hand-holding me through the process.


Dr. Anuradha
E-mail: anuradha2nittur@gmail.com
On Jan 2020

Important Notice

Original article / research
Year : 2022 | Month : April | Volume : 16 | Issue : 4 | Page : QC01 - QC05 Full Version

Identification of Effective Model for Prediction of Ovarian Malignancy Risk using Models like Risk of Malignancy Index, Logistic Regression, International Ovarian Tumour Analysis- Simple Rules


Published: April 1, 2022 | DOI: https://doi.org/10.7860/JCDR/2022/53286.16196
SR Ramya

1. Assistant Professor, Department of Obstetrics and Gynaecology, Karpaga Vinayaga Institute of Medical Sciences and Research Centre, Madhuranthagam, Tamil Nadu, India.

Correspondence Address :
Dr. SR Ramya,
Assistant Professor, Department of Obstetrics and Gynaecology, Karpaga Vinayaga Institute of Medical Sciences and Research Centre, Madhuranthagam, Tamil Nadu, India.
E-mail: amarnageshkumar@gmail.com

Abstract

Introduction: Ovarian tumour is not a single entity it is a spectrum of neoplasm involving variety of histological tissues. Use of mathematical formula as malignancy index which is based on logistic model, menopausal status, serum levels of Cancer Antigen 125 (CA-125) and ultrasound findings in a score system is not so popular which can be a useful predictor for diagnosing and monitoring the progression of ovarian malignancy.

Aim: To determine the effectiveness of the three models i.e., Risk of Malignancy Index (RMI-1,2,3 and 4), Logistic Regression 2 (LR-2), International Ovarian Tumour Analysis (IOTA) - simple rules in predicting ovarian malignancy.

Materials and Methods: This prospective cohort observational study was conducted in Department of Obstetrics and Gynaecology at Saveetha Medical College and Hospital, Tamil Nadu, India, from June 2017 to July 2018. The study included a total of 70 female subjects with ovarian mass. Information obtained by investigations, ultrasound was used to predict the risk of malignancy by using the three models {Risk of Malignancy Index (RMI-1, 2, 3 and 4), Logistic Regression 2 (LR-2), International Ovarian Tumour Analysis (IOTA)- simple rules}. CA-125 level was considered as primary outcome variable. Study group histopathology impression (malignant vs benign) was considered as primary explanatory variable. The result from the above models was compared with the postoperative histopathological report. The sensitivity and specificity of each model was also identified.

Results: Majority of the study participants 49 (70%) were in premenopausal status and only 21 (30%) were in menopausal status. The mean CA-125 level was 108.82±233.13 in the study population (95% CI: 53.23-164.41). Among the 70 study subjects, 53 (75.70%) patients were RMI-1 benign and only 17 (24.30%) were RMI-1 malignant. Majority of the study participants 44 (60%) were IOTA impression benign and only 23 (40%) were IOTA malignant. The difference in the proportion of IOTA-simple rules between histopathology impression was statistically significant (p-value <0.001). The sensitivity of IOTA-simple rules in predicting malignant histopathology was 92%, specificity was 90.48%, diagnostic accuracy was 91.04%.

Conclusion: For early risk stratification of adnexal masses, IOTA-simple rules can be used as a screening tool due to its high sensitivity, specificity, positive predictive value, negative predictive value and diagnostic accuracy.

Keywords

CA-125, Hysterectomy, Index, Malignant tumours, Menopausal status

Ovaries start to develop by the 5th week of intrauterine life. The ovarian differentiation is determined by the presence of a determinant located on the gene of the short arm of X-sex chromosome though the autosomes are also involved in the ovarian development. Two intact sex chromosomes XX are necessary for the development of the ovary (1). Ovarian tumour is not a single entity it is a range of neoplasm including diversity of histological tissues ranging from epithelial tissues, connective tissues, specialized hormone secreting cells to germinal and embryonal cells (1). The most common are epithelial tumours forming 80% of all tumours are benign (1). Of all malignant tumours 90% are epithelial in origin, 80% primary in the ovary and 20% secondary from the breasts, gastrointestinal tracts and colon. Benign tumours can become secondary malignant. The average age of borderline tumours is approximately 46 years (2),(3). Epithelial ovarian cancer is associated with low parity and fertility. Because parity is inversely related to the risk of ovarian cancer, having at least one child is protective for the disease, with risk reduction of 0.3-0.4% (3),(4).

Unopposed oestrogen and obesity are also likely to be risk factor for ovarian tumours (5). The early age of menarche and late menopause are associated with an increase in ovarian cancer risk, because both increase the number of ovulatory cycles (6). Ovulation induction for more than 6 cycles doubles the risk of ovarian carcinoma (7). Most hereditary ovarian cancers result from germ line mutations in the BRCA1 and BRCA2 genes. The development of a mathematical formula using a logistic model, incorporating menopausal status, serum levels of a glycoprotein called CA-125 and ultrasound findings in a score system, has been described in the literature in the form of malignancy index (5),(6),(7). The present study was conducted with an aim to determine the effectiveness of the following three models in the preoperative prediction of risk of ovarian malignancy by comparing the results with the postoperative histopathological report- Risk of Malignancy Index (RMI-1,2,3 and 4), Logistic Regression 2 (LR-2), International Ovarian Tumour Analysis (IOTA)- simple rules. Also, to analyse which model relates best with postoperative histopathological report.

Material and Methods

This prospective cohort observational study was conducted in Department of Obstetrics and Gynaecology at Saveetha Medical College and Hospital, Tamil Nadu, India, from June 2017 to July 2018. The ethical clearance by Institutional Ethics Committee and informed consent by patients included in the study were obtained. Convenient sampling was used for sample selection. Patient with history suggestive of ovarian tumour or ultrasound finding of an ovarian mass and subsequently underwent surgery for the same were included in the study. A total of 70 patients were selected for the study.

Inclusion criteria: Patients presented with ultrasound finding of an ovarian mass (size >5 cm, with internal septations, with solid components, ascites) were included in the study.

Exclusion criteria: Patients presented with physiological cyst (unilateral, simple cyst of <5 cm, with clear fluid), pregnant women, patients who refuse transvaginal ultrasound, those who did not undergo surgical removal of mass at Saveetha Medical College and Hospital, Tamil Nadu, were excluded from the study.

Procedure

A brief history which included the patient’s demographic details was obtained details of general examination, gynaecological examination, per rectal examination were done. Blood investigation for serum CA-125 level was done. About 2 mL of blood was collected from all the subjects, in a red topped plain tube which was used for this biochemical test. First a transabdominal ultrasound was done followed by a transvaginal ultrasound. The findings were entered in the proforma. All the above information was used to predict the malignancy of the ovarian tumour using the three models (RMI-1, 2, 3 and 4, LR-2 and IOTA- simple rule). The result (benign/malignant) from the above models was compared with the postoperative histopathological report, and thereby the most effective model in predicting the malignancy of an ovarian tumour was identified. The histopathological report was taken as standard against which the results from various models were compared. The sensitivity and specificity of each model was also identified.

Risk using models like risk of malignancy index: RMI Index is based on mathematical formula using logistic model, incorporating menopausal status, serum levels of a glycoprotein called CA-125 and ultrasound findings in a score system, in the form of malignancy index. ‘Postmenopause’ is defined as amenorrhoea for more than one year or a woman over 50 years of age who underwent hysterectomy. CA-125 was measured in IU/mL. Ultrasound findings like, bilaterality, multilocularity, solid areas, ascites, intra-abdominal metastasis-one point was given for each feature and the RMI was calculated using the formula RMI=U×M×CA125 U- ultrasound score M- menopausal status CA125 (3),(4),(5).

Logistic regression-2: Model 2 is based on age of the patient (In years), the presence of ascites, the presence of blood flow within a papillary projection, the largest diameter of a solid component (in mm), the irregular internal cyst walls, the presence of acoustic shadow. A value above 0.10 was considered as malignant by LR2 (3),(4),(5).

International ovarian tumour analysis- Simple rules

Ultrasound features for benign and malignant tumours (4),(5),(6):

Benign tumour

• B1-Unilocular cyst
• B2-Presence of solid components, maximum diameter

Malignant tumour

Categorised as follows based on the histopathological features and score

• M1-Irregular solid tumour;
• M2-Presence of ascites;
• M3-Atleast four papillary structures;
• M4-Irregular multilocular solid tumour, maximum diameter >100 mm;
• M5-Very strong blood flow (colour score 4).

Rule

• Rule 1-one or more Malignant features were present in the absence of a benign feature, classified the mass as malignant.
• Rule 2-if one or more benign features were present in the absence of a malignant feature, classified the mass as benign.
• Rule 3- if both malignant and benign features were present, or none of the features was present, the simple rules were inconclusive.

Statistical Analysis

The CA-125 level was considered as primary outcome variable. Study group histopathology impression (malignant vs benign) was considered as primary explanatory variable. Descriptive analysis was carried out by mean and standard deviation for quantitative variables, frequency and proportion for categorical variables. All quantitative variables were checked for normal distribution within each category of explanatory variable by using visual inspection of histograms and normality Q-Q plots. Shapiro-wilk’s test was also conducted to assess normal distribution. Shapiro-wilk’s test p-value of >0.05 was considered as normal distribution. The utility of CA-125 level in predicting malignancy was assessed by Receiver Operative Curve (ROC) analysis. Area under the ROC curve along with it’s 95% Confidence Interval (CI) and p-value was presented. The sensitivity, specificity, predictive values and diagnostic accuracy of the screening tests of RMI-1, RMI-2, RMI-3, RMI-4, LR2 and IOTA-simple rules along with their 95% CI were presented. The p-value <0.05 was considered statistically significant. IBM Statistical Package for the Social Sciences (SPSS) version 22.0 was used for statistical analysis.

Results

A total 70 people were included in the analysis. Majority of the study participants 49 (70%) were in premenopausal status and only 21 (30%) were in menopausal status. The mean CA-125 level was 108.82±233.13 in the study population, minimum level was 5 and maximum level was 1000 (95% CI: 53.23- 164.41). Majority of the study participants 42 (62.70%) were histopathology impression benign and only 25 (35.70%) were histopathology impression malignant. Among all the participants of the study three patients had a borderline tumour in histopathological examination. Therefore, for all comparisons only 67 patients were considered and sensitivity and specificity was calculated accordingly.

Majority of the study participants 52 (71.40%) were RMI-2 benign and only 15 (28.60%) were RMI-2 malignant. Majority of the study participants 54 (75.70%) were RMI-3 benign and only 13 (24.30%) were RMI-3 malignant. Majority of the study participants 52 (71.4%) were RMI-Impression benign and only 15 (28.6%) were RMI-4 malignant. Majority of the study participants 52 (64.30%) were LR-2 impression benign and only 15 (35.70%) were LR-2 malignant. Majority of the study participants 44 (60%) were IOTA impression benign and only 23 (40%) were IOTA malignant.

Among the malignant histopathology, 13 (52%) participants had malignant RMI-1 and remaining 12 (48%) participants had benign. Among the benign histopathology impression, 4 (9.52%) participants had malignant RMI-1 and remaining 38 (90.48%) participants had benign. The difference in the proportion of RMI-1 between histopathology impression was statistically significant (p-value=0.001) (Table/Fig 1).

The sensitivity of RMI-1 in predicting malignant histopathology was 52% (95% CI 31.31% to 72.20%), specificity was 90.48% (95% CI 77.38% to 97.34%) (Table/Fig 2).

Among the malignant histopathology, 15 (60%) participants had malignant RMI-2 and remaining 10 (40%) participants had benign. Among the benign histopathology, 5 (11.9%) participants had malignant RMI-2 and remaining 37 (88.1%) participants had benign. The difference in the proportion of RMI-2 between histopathology impression was statistically significant (p-value <0.001) (Table/Fig 3).

The sensitivity of RMI-2 in predicting malignant histopathology was 60% (95% CI 40.80% to 79.2%), specificity was 88.1% (95% CI 78.31% to 97.9%) (Table/Fig 4).

Among the malignant histopathology impression, 13 (52%) participants had malignant RMI-3 and remaining 12 (48%) participants had benign. Among the benign histopathology impression, 4 (9.5%) participants had malignant RMI-3 and remaining 38 (90.5%) participants had benign. The difference in the proportion of RMI-3 between histopathology impression was statistically significant (p-value <0.001) (Table/Fig 5).

The sensitivity of RMI-3 in predicting malignant histopathology was 52% (95% CI 32.42% to 71.6%), specificity was 90.5% (95% CI 81.63% to 99.4%) (Table/Fig 6).

Among the malignant histopathology impression, 15 (60%) participants had malignant RMI-4 and remaining 10 (40%) participants had benign.

Among the benign histopathology impression, 5 (11.9%) participants had malignant RMI-4 and remaining 37 (88.1%) participants had benign. The difference in the proportion of RMI-4 impression between histopathology impression was statistically significant (p-value <0.001) (Table/Fig 3).

The sensitivity of RMI-4 impression in predicting malignant histopathology was 60% (95% CI 40.80% to 79.2%), specificity was 88.1% (95% CI 78.31% to 97.9%) (Table/Fig 4).

Among the malignant histopathology impression, 15 (60%) participants had malignant LR-2 and remaining 10 (40%) participants had benign. Among the benign histopathology impression, 5 (11.9%) participants had malignant LR-2 and 37 (88.1%) participants had benign. The difference in the proportion of LR-2 between histopathology impression was statistically significant (p-value <0.001) (Table/Fig 7).

The sensitivity of LR-2 in predicting malignant histopathology was 76% (95% CI 54.87% to 90.64%), Specificity was 88.10% (95% CI 74.37% to 96.02%) (Table/Fig 8).

Among the malignant histopathology impression, 23 (92%) participants had malignant IOTA-simple rules and remaining 2(8%) participants had benign. Among the benign histopathology impression, 4 (9.52%) participants had malignant IOTA-simple rules and remaining 38 (90.48%) participants had benign. The difference in the proportion of IOTA-simple rules between histopathology impression was statistically significant (p-value <0.001) (Table/Fig 9).

The sensitivity of IOTA-simple rules in predicting malignant histopathology was 92% (95% CI 73.97% to 99.02%), specificity was 90.48% (95% CI 77.38% to 97.34%) (Table/Fig 10).

The CA-125 level had fair predictive validity in predicting malignant, as indicated by area under the curve of 0.773 (95% CI 0.655 to 0.891, p-value <0.001) (Table/Fig 11).

Discussion

A total of 70 women were included in the final analysis. Among the study population, 30% of the women had attained menopause. 70% of the women were premenopausal. In the study by Javdekar R and Maitra N 2015 (6), 58.5% were premenopausal and 41.5% of the women were postmenopausal. The mean CA-125 levels among the study population were 108.82 U/mL. There was a wide variability in the CA-125 levels ranging from as low as 5 U/mL to as high as 1000 U/mL. The median value was 18.90 U/mL which was much less than the mean, indicating that the distribution was right skewed (6). In the study by Zurawski VR Jr et al., for assessing the utility of CA-125 in predicting ovarian cancer, the median level of CA-125 among the cases was 18 U/Ml (7). In the study by Helzlsouer KJ et al., the median level of CA-125 at the time of diagnosis was 35.4U/mL which is higher than the current study (8). In the study by Javdekar R and Maitra N, among those with benign tumours, the mean CA-125 levels was 33 U/mL and median CA-125 levels was 13 U/mL (6). Among those who had malignant ovarian tumours, the mean CA-125 levels were 395 U/mL and the median CA-125 level was 329 U/mL.

The diagnostic accuracy of RMI 1 the present study is similar to that of the study by Karimi-Zarchi M et al., (Table/Fig 12) (9).

The overall diagnostic accuracy of RMI 2 was 77.6%. The diagnostic accuracy in this present study is comparable to the study by Karimi-Zarchi M et al., (9). The sensitivity and PPV of this study are lower when compared to other studies (7),(8),(9). The specificity of this study is comparable to the studies by Yamamoto Y et al., Javdekar R and Maitra N, van den Akker PA et al., Obeidat BR et al., 2004 and the specificity is lower compared to the study by Manjunath AP et al., [4,6,10-12]. The PPV is comparable to the study by Javdekar R and Maitra N and lower than the studies by Obeidat BR et al., Yamamoto Y et al., and Manjunath AP et al., (4),(6),(11),(12). The NPV is comparable to the study by Obeidat BR et al., and higher than the study by Manjunath AP et al., (11),(12). The NPV is lower than the studies by Javdkar and Maitra, Karimi-Zarchi M et al., and van den Akker PA et al., (6),(9),(10). The comparisons are given in (Table/Fig 13).

The specificity of this current study is a little lower than the study by Sayasneh A et al., and higher than the study by Karimi-Zarchi M et al., (9),(13). There was also a very low false positive rate of 11.9%.

The sensitivity of RMI-3 was lower than RMI-2 at 52%. The sensitivity of this current study is much lower than the studies by Karimi-Zarchi M et al., and Sayasneh A et al., (9),(13). The PPV in the current study is higher and NPV is lower than the study by Karimi-Zarchi M et al., (9). The diagnostic accuracy however is similar to the study by Karimi-Zarchi M et al., (9).

Similar to RMI 4, LR-2 was also found to be a good rule out test due to the high specificity of 88.10% and a low false positive rate of 11.90%. The specificity of RMI-1 to RMI-4 and LR-2 of this study is comparable to the study by Sayasneh A et al., and higher compared to Nunes N et al., Testa A et al., and Nunes N et al., (13),(14),(15),(16). However, the sensitivity was low at 76% and false negatives rate was high at 24%. The sensitivity of the current study is much lower compared to other studies by Nunes N et al., Sayasneh A et al., (13), Testa A et al., and Nunes N et al., (13),(14),(15),(17).

Compared to RMI-1,2,3,4 and LR-2 models, IOTA model had the highest level of significant association with histopathological confirmation. The sensitivity of IOTA model in this current study is comparable to the studies by Kaijser J et al., (sensitivity 90%, specificity 93%), Nunes N et al., (the pooled sensitivity was 93% and the pooled specificity was 95%) and Garg S et al., (sensitivity 93% and specificity was 80%) (17),(18),(19). The sensitivity is higher than the study by Tantipalakom C et al., (sensitivity 82.9%) and lower than the study by Testa A et al., (sensitivity 67%, specificity 91%) (15),(20). The specificity is higher than the studies by Testa A et al., and Garg S et al., (values were mentioned above) (15),(19). The specificity is lower than the studies by Kaijser J et al., Nunes N et al., 2014 and Tantipalakom C et al., (17),(18),(20). The diagnostic accuracy of the current study is higher than the study by Garg S et al., (19).

CA-125 levels had a fair predictive value in predicting malignancy as indicated by a 77.3% area under the ROC curve. The area under curve for CA-125 according to the study by Mehri JS et al., was 63.3% (21). Hence, comparing all scoring systems for predicting malignancy, IOTA-simple rules was found to have the highest level of sensitivity and specificity along with low false positive and false negative rates.

Limitation(s)

As, the sample size of the study was less multicentric studies with large sample size can be planned, for affirmative conclusions which can be accepted by the researchers across the world.

Conclusion

Early diagnosis of ovarian cancer is crucial for timely management. In the current study population, only one-fourth were suspected to have malignant ovarian tumours. However, IOTA-simple rules were found to be superior to LR-2 with the highest level of sensitivity and specificity. Hence, for early risk stratification of adnexal masses and for deciding the type of surgery, IOTA-simple rules can be used as a screening tool due to its high sensitivity, specificity, PPV, NPV and diagnostic accuracy. This would aid in better patient management, thereby reducing complications and improved survival.

Acknowledgement

Authors would like to thank, the Managing Director and Trustee, Dr. R Annamalai; M.S., M.Ch of Karpaga Vinayga Institute of Medical Sciences and Research Centre, Madhuranthagam, Tamil Nadu, India, for his encouragement and support in accomplishing this project.

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DOI and Others

DOI: 10.7860/JCDR/2022/53286.16196

Date of Submission: Nov 13, 2021
Date of Peer Review: Jan 06, 2021
Date of Acceptance: Feb 15, 2022
Date of Publishing: Apr 01, 2022

AUTHOR DECLARATION:
• Financial or Other Competing Interests: None
• Was Ethics Committee Approval obtained for this study? Yes
• Was informed consent obtained from the subjects involved in the study? Yes
• For any images presented appropriate consent has been obtained from the subjects. NA

PLAGIARISM CHECKING METHODS:
• Plagiarism X-checker: Nov 16, 2021
• Manual Googling: Feb 14, 2022
• iThenticate Software: Feb 22, 2022 (19%)

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