Displaying publications 81 - 100 of 160 in total

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  1. Menon R
    Med J Malaya, 1971 Mar;25(3):226-8.
    PMID: 4253254
    Matched MeSH terms: Ovarian Neoplasms*
  2. Rima Melati Mat Satar, Zed Zakari Abdul Hamid, Hartini Yusuf, Maimunah Mustakim
    MyJurnal
    Ki-67 expression is strongly correlated with tumour cell proliferation and growth. It is widely used as a proliferation marker in the routine pathological investigation. The nuclear protein Ki- 67 (pKi67) is recognised prognostic and predictive indicator for the biopsies assessment for cancer patients. Clinically, pKi67 has been revealed to associate with metastasis and the clinical stage of tumours. Furthermore, it has been presented that the expression of Ki-67 is significantly higher in malignant tissues with poorly differentiated tumour cells, as compared with normal tissue. The Ki-67 labelling index plays a vital role as an independent prognostic factor for survival rate, which includes all stages and grade categories. There is an association between the ratios of Ki-67 positive malignant cells and patient survival. This review provides an overview of recent advances in detecting Ki-67 in ovarian carcinoma.
    Matched MeSH terms: Ovarian Neoplasms
  3. Mokhtar N, Thevarajah M, Ma N, M I
    Asian Pac J Cancer Prev, 2012;13(12):6391-5.
    PMID: 23464464
    BACKGROUND: Ovarian cancer is ranked as the fifth most common cause of cancer death in women. In Malaysia, it is the fourth most common cancer in females. CA125 has been the tumor marker of choice in ovarian cancer but its diagnostic specificity in early stages is only 50%. Hence, there is a critical need to identify an alternative tumor marker that is capable of detecting detect ovarian cancer at an early stage. HE4 is a new tumor marker proposed for the early diagnosis of ovarian cancer and disease recurrence. Currently, none of the normal ranges of HE4 quoted in the literature are based on data for a multiethnic Asian population. Therefore, the aim of this study was to determine reference intervals for HE4 in an Asian population presenting in University Malaya Medical Centre, a tertiary reference hospital.

    MATERIALS AND METHODS: 300 healthy women were recruited comprising 150 premenopausal and 150 postmenopausal women, aged from 20-76 years. All women were subjected to a pelvic ultrasonograph and were confirmed to be free from ovarian pathology on recruitment. Serum HE4 levels were determined by chemiluminescent microparticle immunoassay (CMIA, Abbott Architect). The reference intervals were determined following CLSI guidelines (C28-A2) using a non-parametric method.

    RESULTS: The upper limits of the 95th percentile reference interval (90%CI) for all the women collectively were 64.6 pmol/L, and 58.4 pmol/L for premenopausal) and 69.0 pmol/L for postmenopausal. The concentration of HE4 was noted to increase with age especially in women who were more than 50 years old. We also noted that our proposed reference limit was lower compared to the level given by manufacturer Abbott Architect HE4 kit insert (58.4 vs 70 pmol/L for premenopausal group and 69.0 vs 140 pmol/L in the postmenopausal group). The study also showed a significant difference in HE4 concentrations between ethnic groups (Malays and Indians). The levels of HE4 in Indians appeared higher than in Malays (p<0.05), while no significant differences were noted between the Malays and Chinese ethnic groups.

    CONCLUSIONS: More data are needed to establish a reference interval that will better represent the multiethnic Malaysian population. Probably a larger sampling size of equal representation of the Malay, Chinese, Indians as well as the other native ethnic communities will give us a greater confidence on whether genetics plays a role in reference interval determination.

    Matched MeSH terms: Ovarian Neoplasms/diagnosis*; Ovarian Neoplasms/metabolism
  4. Yang Y, Wu L, Shu X, Lu Y, Shu XO, Cai Q, et al.
    Cancer Res, 2019 Feb 01;79(3):505-517.
    PMID: 30559148 DOI: 10.1158/0008-5472.CAN-18-2726
    DNA methylation is instrumental for gene regulation. Global changes in the epigenetic landscape have been recognized as a hallmark of cancer. However, the role of DNA methylation in epithelial ovarian cancer (EOC) remains unclear. In this study, high-density genetic and DNA methylation data in white blood cells from the Framingham Heart Study (N = 1,595) were used to build genetic models to predict DNA methylation levels. These prediction models were then applied to the summary statistics of a genome-wide association study (GWAS) of ovarian cancer including 22,406 EOC cases and 40,941 controls to investigate genetically predicted DNA methylation levels in association with EOC risk. Among 62,938 CpG sites investigated, genetically predicted methylation levels at 89 CpG were significantly associated with EOC risk at a Bonferroni-corrected threshold of P < 7.94 × 10-7. Of them, 87 were located at GWAS-identified EOC susceptibility regions and two resided in a genomic region not previously reported to be associated with EOC risk. Integrative analyses of genetic, methylation, and gene expression data identified consistent directions of associations across 12 CpG, five genes, and EOC risk, suggesting that methylation at these 12 CpG may influence EOC risk by regulating expression of these five genes, namely MAPT, HOXB3, ABHD8, ARHGAP27, and SKAP1. We identified novel DNA methylation markers associated with EOC risk and propose that methylation at multiple CpG may affect EOC risk via regulation of gene expression. SIGNIFICANCE: Identification of novel DNA methylation markers associated with EOC risk suggests that methylation at multiple CpG may affect EOC risk through regulation of gene expression.
    Matched MeSH terms: Ovarian Neoplasms/genetics*
  5. Lu Y, Beeghly-Fadiel A, Wu L, Guo X, Li B, Schildkraut JM, et al.
    Cancer Res, 2018 Sep 15;78(18):5419-5430.
    PMID: 30054336 DOI: 10.1158/0008-5472.CAN-18-0951
    Large-scale genome-wide association studies (GWAS) have identified approximately 35 loci associated with epithelial ovarian cancer (EOC) risk. The majority of GWAS-identified disease susceptibility variants are located in noncoding regions, and causal genes underlying these associations remain largely unknown. Here, we performed a transcriptome-wide association study to search for novel genetic loci and plausible causal genes at known GWAS loci. We used RNA sequencing data (68 normal ovarian tissue samples from 68 individuals and 6,124 cross-tissue samples from 369 individuals) and high-density genotyping data from European descendants of the Genotype-Tissue Expression (GTEx V6) project to build ovarian and cross-tissue models of genetically regulated expression using elastic net methods. We evaluated 17,121 genes for their cis-predicted gene expression in relation to EOC risk using summary statistics data from GWAS of 97,898 women, including 29,396 EOC cases. With a Bonferroni-corrected significance level of P < 2.2 × 10-6, we identified 35 genes, including FZD4 at 11q14.2 (Z = 5.08, P = 3.83 × 10-7, the cross-tissue model; 1 Mb away from any GWAS-identified EOC risk variant), a potential novel locus for EOC risk. All other 34 significantly associated genes were located within 1 Mb of known GWAS-identified loci, including 23 genes at 6 loci not previously linked to EOC risk. Upon conditioning on nearby known EOC GWAS-identified variants, the associations for 31 genes disappeared and three genes remained (P < 1.47 × 10-3). These data identify one novel locus (FZD4) and 34 genes at 13 known EOC risk loci associated with EOC risk, providing new insights into EOC carcinogenesis.Significance: Transcriptomic analysis of a large cohort confirms earlier GWAS loci and reveals FZD4 as a novel locus associated with EOC risk. Cancer Res; 78(18); 5419-30. ©2018 AACR.
    Matched MeSH terms: Ovarian Neoplasms/genetics*
  6. Liang T, Qu Q, Chang Y, Gopinath SCB, Liu XT
    Biotechnol Appl Biochem, 2019 Nov;66(6):939-944.
    PMID: 31468573 DOI: 10.1002/bab.1808
    Ovarian cancer starts in the ovaries in its earlier stages and then spreads to the pelvis, uterus, and abdominal region. The success of an ovarian cancer treatment depends on the stage of the cancer and the diagnostic system. Squamous cell carcinoma antigen (SCC-Ag) is one of the most efficient cancer biomarkers, and elevated levels of SCC-Ag in ovarian cancer cells have been used to identify ovarian cancer. Carbon is a potential material for biosensing applications due to its thermal, electrical, and physical properties. Multiwalled carbon nanotubes (MWCNTs) are carbon-based materials that can be used here to detect SCC-Ag. Anti-SCC-Ag antibody was immobilized on the amine-modified MWCNT dielectric sensing surface to detect SCC-Ag. The uniformity of the surface structure was measured with a 3D nanoprofiler, and the results confirmed the detection of SCC-Ag at ∼80 pM. The specific detection of SCC-Ag was confirmed with two control proteins (factor IX and human serum albumin), and the system did not show biofouling. This experimental set-up with MWCNTs a dielectric sensing surface can lead to the detection of ovarian cancer in its initial stages.
    Matched MeSH terms: Ovarian Neoplasms
  7. Chaw SH, Foo LL, Chan L, Wong KK, Abdullah S, Lim BK
    Rev Bras Anestesiol, 2016 09 28;67(6):647-650.
    PMID: 27687317 DOI: 10.1016/j.bjan.2016.09.003
    Anti-N-methyl-d-aspartate receptor encephalitis is a recently described neurological disorder and an increasingly recognized cause of psychosis, movement disorders and autonomic dysfunction. We report 20-year-old Chinese female who presented with generalized tonic-clonic seizures, recent memory loss, visual hallucinations and abnormal behavior. Anti-N-methyl-d-aspartate receptor encephalitis was diagnosed and a computed tomography scan of abdomen reviewed a left adnexal tumor. We describe the first such case report of a patient with anti-N-methyl-d-aspartate receptor encephalitis who was given a bilateral transversus abdominis plane block as the sole anesthetic for removal of ovarian tumor. We also discuss the anesthetic issues associated with anti-N-methyl-d-aspartate receptor encephalitis. As discovery of tumor and its removal is the focus of initial treatment in this group of patients, anesthetists will encounter more such cases in the near future.
    Matched MeSH terms: Ovarian Neoplasms/complications; Ovarian Neoplasms/surgery
  8. Yarmolinsky J, Relton CL, Lophatananon A, Muir K, Menon U, Gentry-Maharaj A, et al.
    PLoS Med, 2019 Aug;16(8):e1002893.
    PMID: 31390370 DOI: 10.1371/journal.pmed.1002893
    BACKGROUND: Various risk factors have been associated with epithelial ovarian cancer risk in observational epidemiological studies. However, the causal nature of the risk factors reported, and thus their suitability as effective intervention targets, is unclear given the susceptibility of conventional observational designs to residual confounding and reverse causation. Mendelian randomization (MR) uses genetic variants as proxies for risk factors to strengthen causal inference in observational studies. We used MR to evaluate the association of 12 previously reported risk factors (reproductive, anthropometric, clinical, lifestyle, and molecular factors) with risk of invasive epithelial ovarian cancer, invasive epithelial ovarian cancer histotypes, and low malignant potential tumours.

    METHODS AND FINDINGS: Genetic instruments to proxy 12 risk factors were constructed by identifying single nucleotide polymorphisms (SNPs) that were robustly (P < 5 × 10-8) and independently associated with each respective risk factor in previously reported genome-wide association studies. These risk factors included genetic liability to 3 factors (endometriosis, polycystic ovary syndrome, type 2 diabetes) scaled to reflect a 50% higher odds liability to disease. We obtained summary statistics for the association of these SNPs with risk of overall and histotype-specific invasive epithelial ovarian cancer (22,406 cases; 40,941 controls) and low malignant potential tumours (3,103 cases; 40,941 controls) from the Ovarian Cancer Association Consortium (OCAC). The OCAC dataset comprises 63 genotyping project/case-control sets with participants of European ancestry recruited from 14 countries (US, Australia, Belarus, Germany, Belgium, Denmark, Finland, Norway, Canada, Poland, UK, Spain, Netherlands, and Sweden). SNPs were combined into multi-allelic inverse-variance-weighted fixed or random effects models to generate effect estimates and 95% confidence intervals (CIs). Three complementary sensitivity analyses were performed to examine violations of MR assumptions: MR-Egger regression and weighted median and mode estimators. A Bonferroni-corrected P value threshold was used to establish strong evidence (P < 0.0042) and suggestive evidence (0.0042 < P < 0.05) for associations. In MR analyses, there was strong or suggestive evidence that 2 of the 12 risk factors were associated with invasive epithelial ovarian cancer and 8 of the 12 were associated with 1 or more invasive epithelial ovarian cancer histotypes. There was strong evidence that genetic liability to endometriosis was associated with an increased risk of invasive epithelial ovarian cancer (odds ratio [OR] per 50% higher odds liability: 1.10, 95% CI 1.06-1.15; P = 6.94 × 10-7) and suggestive evidence that lifetime smoking exposure was associated with an increased risk of invasive epithelial ovarian cancer (OR per unit increase in smoking score: 1.36, 95% CI 1.04-1.78; P = 0.02). In analyses examining histotypes and low malignant potential tumours, the strongest associations found were between height and clear cell carcinoma (OR per SD increase: 1.36, 95% CI 1.15-1.61; P = 0.0003); age at natural menopause and endometrioid carcinoma (OR per year later onset: 1.09, 95% CI 1.02-1.16; P = 0.007); and genetic liability to polycystic ovary syndrome and endometrioid carcinoma (OR per 50% higher odds liability: 0.89, 95% CI 0.82-0.96; P = 0.002). There was little evidence for an association of genetic liability to type 2 diabetes, parity, or circulating levels of 25-hydroxyvitamin D and sex hormone binding globulin with ovarian cancer or its subtypes. The primary limitations of this analysis include the modest statistical power for analyses of risk factors in relation to some less common ovarian cancer histotypes (low grade serous, mucinous, and clear cell carcinomas), the inability to directly examine the association of some ovarian cancer risk factors that did not have robust genetic variants available to serve as proxies (e.g., oral contraceptive use, hormone replacement therapy), and the assumption of linear relationships between risk factors and ovarian cancer risk.

    CONCLUSIONS: Our comprehensive examination of possible aetiological drivers of ovarian carcinogenesis using germline genetic variants to proxy risk factors supports a role for few of these factors in invasive epithelial ovarian cancer overall and suggests distinct aetiologies across histotypes. The identification of novel risk factors remains an important priority for the prevention of epithelial ovarian cancer.

    Matched MeSH terms: Ovarian Neoplasms/etiology*; Ovarian Neoplasms/genetics
  9. Velapasamy S, Alex L, Chahil JK, Lye SH, Munretnam K, Hashim NA, et al.
    Genet Test Mol Biomarkers, 2013 Jan;17(1):62-8.
    PMID: 23113749 DOI: 10.1089/gtmb.2012.0223
    The identification of high-risk individuals can help to improve early cancer detection and patient survival. Risk assessment, however, can only be accomplished if the risk factors are known. To date, the genetic risk factors for ovarian cancer, other than mutations in the BRCA1/2 genes, have never been systematically explored in Malaysia. The present study aims to identify from a panel of cancer-associated single-nucleotide polymorphisms (SNPs), those associated with ovarian cancer risk in Malaysia.
    Matched MeSH terms: Ovarian Neoplasms/genetics*; Ovarian Neoplasms/epidemiology
  10. Kar SP, Beesley J, Amin Al Olama A, Michailidou K, Tyrer J, Kote-Jarai Z, et al.
    Cancer Discov, 2016 Sep;6(9):1052-67.
    PMID: 27432226 DOI: 10.1158/2159-8290.CD-15-1227
    Breast, ovarian, and prostate cancers are hormone-related and may have a shared genetic basis, but this has not been investigated systematically by genome-wide association (GWA) studies. Meta-analyses combining the largest GWA meta-analysis data sets for these cancers totaling 112,349 cases and 116,421 controls of European ancestry, all together and in pairs, identified at P < 10(-8) seven new cross-cancer loci: three associated with susceptibility to all three cancers (rs17041869/2q13/BCL2L11; rs7937840/11q12/INCENP; rs1469713/19p13/GATAD2A), two breast and ovarian cancer risk loci (rs200182588/9q31/SMC2; rs8037137/15q26/RCCD1), and two breast and prostate cancer risk loci (rs5013329/1p34/NSUN4; rs9375701/6q23/L3MBTL3). Index variants in five additional regions previously associated with only one cancer also showed clear association with a second cancer type. Cell-type-specific expression quantitative trait locus and enhancer-gene interaction annotations suggested target genes with potential cross-cancer roles at the new loci. Pathway analysis revealed significant enrichment of death receptor signaling genes near loci with P < 10(-5) in the three-cancer meta-analysis.

    SIGNIFICANCE: We demonstrate that combining large-scale GWA meta-analysis findings across cancer types can identify completely new risk loci common to breast, ovarian, and prostate cancers. We show that the identification of such cross-cancer risk loci has the potential to shed new light on the shared biology underlying these hormone-related cancers. Cancer Discov; 6(9); 1052-67. ©2016 AACR.This article is highlighted in the In This Issue feature, p. 932.

    Matched MeSH terms: Ovarian Neoplasms/genetics*
  11. Pawar S, Liew TO, Stanam A, Lahiri C
    Chem Biol Drug Des, 2020 09;96(3):995-1004.
    PMID: 32410355 DOI: 10.1111/cbdd.13672
    Biomarkers can offer great promise for improving prevention and treatment of complex diseases such as cancer, cardiovascular diseases, and diabetes. These can be used as either diagnostic or predictive or as prognostic biomarkers. The revolution brought about in biological big data analytics by artificial intelligence (AI) has the potential to identify a broader range of genetic differences and support the generation of more robust biomarkers in medicine. AI is invigorating biomarker research on various fronts, right from the cataloguing of key mutations driving the complex diseases like cancer to the elucidation of molecular networks underlying diseases. In this study, we have explored the potential of AI through machine learning approaches to propose that these methods can act as recommendation systems to sort and prioritize important genes and finally predict the presence of specific biomarkers. Essentially, we have utilized microarray datasets from open-source databases, like GEO, for breast, lung, colon, and ovarian cancer. In this context, different clustering analyses like hierarchical and k-means along with random forest algorithm have been utilized to classify important genes from a pool of several thousand genes. To this end, network centrality and pathway analysis have been implemented to identify the most potential target as CREB1.
    Matched MeSH terms: Ovarian Neoplasms/metabolism*
  12. Kothare SN
    Singapore Med J, 1980 Dec;21(6):756-9.
    PMID: 7221588
    This is an analysis of ovarian neoplasms encountered in Sarawak during the period January 1976-December 1977. There were 149 benign and 36 primary malignant tumours with an incidence of 44.3 per cent and 23.6 per cent respectively, in neoplasms 01 the Reproductive System. Amongst the benign ovarian tumours Dermoid Cyst
    (Cystic Teratoma) was quite frequent (29.5 per cent). In malignant neoplasms Cystadenocarcinomas constituted 66.7 per cent of the total. A case each of Granulosa cell earcinoma, Adenoacanthoma and Endodermal sinus tumours, 4 of Dysgerminoma and 6 of metastatic ovarian tumours were also recorded.
    Matched MeSH terms: Ovarian Neoplasms/epidemiology*; Ovarian Neoplasms/pathology
  13. Park SJ, Lee EJ, Lee TS, Wang KL, Okamoto A, Ochiai K, et al.
    Eur J Surg Oncol, 2021 05;47(5):1111-1116.
    PMID: 33303297 DOI: 10.1016/j.ejso.2020.11.012
    PURPOSE: We performed an E-survey to evaluate the practice patterns in debulking surgery for advanced ovarian cancer in Asia.

    METHODS: We designed a questionnaire, including 50 questions related to debulking surgery for advanced ovarian cancer. The questionnaire was sent to Gynecologic Oncologic Groups in Asia from December 2016 to February 2017.

    RESULTS: A total of 253 gynecologic oncologists from Japan (58.9%), the Republic of Korea (19%), Taiwan (12.6%), and the other counties including China (7.5%), Malaysia (0.8%), Indonesia (0.8%), and Thailand (0.4%) participated in this E-survey. The median number of debulking surgeries per year was 20, and 46.8% of the respondents preferred <1 cm as the criterion for optimal debulking surgery (ODS). The most common barrier and surgical finding precluding ODS were performance status (74.3%) and disease involving the porta hepatis (71.5%). Moreover, 63.2% had a fellowship program, and only 15% or less had opportunities to receive additional training courses in general, thoracic, or urologic surgery. The median percentage of patients receiving neoadjuvant chemotherapy (NAC) was 30%, and the achieved rate of ODS in primary debulking surgery (PDS) and interval debulking surgery (IDS) was 65% and 80%, respectively. Most of the respondents required three to 6 h for PDS (48.6%) and IDS (58.9%). Moreover, more than 50% depended on ultra-radical surgery conducted by specialists.

    CONCLUSIONS: The ODS criteria are relatively lenient with a preference for NAC in 30% of the respondents in Asia. This trend might be associated with the dependence on aggressive surgery performed by specialists.

    Matched MeSH terms: Ovarian Neoplasms/surgery*
  14. Khoo SY
    J Palliat Med, 2013 Jun;16(6):703.
    PMID: 23614714 DOI: 10.1089/jpm.2012.0428
    Matched MeSH terms: Ovarian Neoplasms/physiopathology
  15. Khoo JJ
    Med J Malaysia, 2002 Jun;57(2):161-8.
    PMID: 24326646
    Borderline epithelial tumours or low malignant potential epithelial tumours of ovary have a better prognosis and hence it is important to distinguish this group from their malignant counterparts. Several studies were done correlate the growth rates of tumours with nuclear proteins that are expressed in proliferating cells. Immunohistochemical stains with monoclonal antibodies against proliferating cell nuclear antigen (PCNA) were used on 51 archival epithelial tumours of ovary. The percentage of PCNA reactivity showed means of 1.1%, 2.3% and 27.7% with benign, borderline tumours and malignant epithelial tumours of ovary. respectively. The % PCNA reactivity was found to be significantly different amongst the three group (p<0.001). Thus , PCNA reactivity can help to differentiate borderline tumours from malignant epithelial tumours of ovary. This is critical when light microscopic appearances are equivocal and therapeutic management is dependent on the diagnosis.
    Matched MeSH terms: Ovarian Neoplasms
  16. Shafiee MN, Kah Teik C, Md Zain RR, Kampan N
    Horm Mol Biol Clin Investig, 2019 Aug 09;41(2).
    PMID: 31398145 DOI: 10.1515/hmbci-2019-0037
    Uterine leiomyosarcoma (LMS) is rare but primary ovarian LMS is even rarer constituting less than 0.1% of all gynecologic disorders. Neither histologic features nor immunohistochemistry could be utilized to distinguish between uterine or ovarian origin. We illustrate a clinical case of metastatic LMS to the ovary in a woman with underlying uterine fibroid presenting with anemia with heavy menses.
    Matched MeSH terms: Ovarian Neoplasms/diagnosis*; Ovarian Neoplasms/etiology; Ovarian Neoplasms/therapy
  17. Fortner RT, Ose J, Merritt MA, Schock H, Tjønneland A, Hansen L, et al.
    Int J Cancer, 2015 Sep 01;137(5):1196-208.
    PMID: 25656413 DOI: 10.1002/ijc.29471
    Whether risk factors for epithelial ovarian cancer (EOC) differ by subtype (i.e., dualistic pathway of carcinogenesis, histologic subtype) is not well understood; however, data to date suggest risk factor differences. We examined associations between reproductive and hormone-related risk factors for EOC by subtype in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. Among 334,126 women with data on reproductive and hormone-related risk factors (follow-up: 1992-2010), 1,245 incident cases of EOC with known histology and invasiveness were identified. Data on tumor histology, grade, and invasiveness, were available from cancer registries and pathology record review. We observed significant heterogeneity by the dualistic model (i.e., type I [low grade serous or endometrioid, mucinous, clear cell, malignant Brenner] vs. type II [high grade serous or endometrioid]) for full-term pregnancy (phet  = 0.02). Full-term pregnancy was more strongly inversely associated with type I than type II tumors (ever vs. never: type I: relative risk (RR) 0.47 [95% confidence interval (CI): 0.33-0.69]; type II, RR: 0.81 [0.61-1.06]). We observed no significant differences in risk in analyses by major histologic subtypes of invasive EOC (serous, mucinous, endometrioid, clear cell). None of the investigated factors were associated with borderline tumors. Established protective factors, including duration of oral contraceptive use and full term pregnancy, were consistently inversely associated with risk across histologic subtypes (e.g., ever full-term pregnancy: serous, RR: 0.73 [0.58-0.92]; mucinous, RR: 0.53 [0.30-0.95]; endometrioid, RR: 0.65 [0.40-1.06]; clear cell, RR: 0.34 [0.18-0.64]; phet  = 0.16). These results suggest limited heterogeneity between reproductive and hormone-related risk factors and EOC subtypes.
    Matched MeSH terms: Ovarian Neoplasms/epidemiology; Ovarian Neoplasms/pathology*; Ovarian Neoplasms/prevention & control*
  18. Sachdev Manjit Singh B, Wan SA, Cheong YK, Chuah SL, Teh CL, Jobli AT
    J Med Case Rep, 2021 Feb 23;15(1):94.
    PMID: 33618728 DOI: 10.1186/s13256-020-02642-z
    BACKGROUND: Arthritis is rarely reported as a paraneoplastic manifestation of occult malignancy. We report herein two cases of paraneoplastic arthritis due to occult malignancy. CASE 1: The patient was a 65-year-old woman of asian descent who was a former smoker with a history of spine surgery performed for L4/L5 degenerative disc disease. She presented with a 1-month history of oligoarthritis affecting both ankle joints and early morning stiffness of about 3 hours. Laboratory tests were positive for antinuclear antibody at a titer of 1:320 (speckled) but negative for rheumatoid factor. She was treated for seronegative spondyloarthritis and started on prednisolone without much improvement. A routine chest radiograph incidentally revealed a right lung mass which was found to be adenocarcinoma of the lung. She was treated with gefitinib and her arthritis resolved. CASE 2: The patient was a 64-year-old woman of asian descent, nonsmoker, who presented with a chief complaint of asymmetrical polyarthritis involving her right wrist, second and third metacarpophalangeal joints, and first to fifth proximal interphalangeal joints. She was treated for seronegative rheumatoid arthritis (RA) and started on sulfasalazine, with poor clinical response. Six months later, she developed abdominal pain which was diagnosed as ovarian carcinoma by laparotomy. Her arthritis resolved following treatment of her malignancy with chemotherapy.

    CONCLUSION: In summary, paraneoplastic arthritis usually presents in an atypical manner and responds poorly to disease-modifying antirheumatic drugs. Accordingly, we recommend screening for occult malignancy in patients presenting with atypical arthritis.

    Matched MeSH terms: Ovarian Neoplasms/diagnosis; Ovarian Neoplasms/drug therapy
  19. Song HJ, Kim JD, Park CY, Kim YS, Jeong KS
    Sains Malaysiana, 2015;44:1671-1676.
    This study compares the diagnostic performance of urine and serum multiple biomarkers for early diagnosis of ovarian
    cancer. The sample population includes 119 benign and 101 ovarian cancer patients. The marker combinations used
    to compare performance include 16 markers whose concentration values were obtained using the Luminex assay. In
    order to identify an optimal marker combination that could classify ovarian cancer and benign patients, the area under
    the curve (AUC) is used to evaluate 2-, 3-, and 4-marker combinations and the classification is performed by using
    logistic regression. In the case of urine samples, the best AUC values are 87.89% for the 2 protein markers combination,
    90.22% for the 3 markers combination, and 92.43% for the 4 marker combination. In contrast, the best AUC values
    for serum sample are 92.4% for the 2 marker combination, 93.63% for the 3 marker combination and 94.63% for the
    4 marker combination. This study confirmed that combining multiple biomarkers could improve diagnostic accuracy.
    Even though the urine sample shows relatively lower performance than serum, urine could be utilized more widely for
    its simple usability.
    Matched MeSH terms: Ovarian Neoplasms
  20. Shekhar KC, Soh EBS, Jayalakshmi P
    Med J Malaysia, 2000 Sep;55(3):371-5.
    PMID: 11200720
    Schistosomiasis is a widely prevalent disease in the world and usually involves the gastro-intestinal and urinary tract. The involvement of the female genital tract has been well-established in S. haematobium infections and is rare with S. japonicum infections. This case involves a Filipino female who was admitted to the University Hospital Kuala Lumpur for right iliac fossa pain and was diagnosed initially as acute appendicitis. Ultrasound showed a multi-septated pelvic cyst leading to a provisional diagnosis of ovarian torsion. Intraoperatively a right parovarian cyst was detected and removed. Histology revealed a congested cyst wall with areas of haemorrhage with several viable and calcified eggs of S. japonicum measuring 85 microns x 62 microns. Within the cystic cavity blood admixed with eggs were seen. Confirmation was carried out by using the indirect haemagglutination (IHA) test. This is a first report of upper genital schistosomiasis mimicking an ovarian tumour.
    Matched MeSH terms: Ovarian Neoplasms/diagnosis*
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