Salivary Lactate Dehydrogenase (LDH)- A Novel Technique in Oral Cancer Detection and Diagnosis

医学 乳酸脱氢酶 恶性肿瘤 内科学 胃肠病学 癌症 基底细胞 生物标志物 病理 肿瘤科 生物 生物化学
作者
Kavyashree Lokesh,Jayanthi Kannabiran,Rajesh P. N. Rao
出处
期刊:Journal of Clinical and Diagnostic Research [JCDR Research and Publications Private Limited]
被引量:18
标识
DOI:10.7860/jcdr/2016/16243.7223
摘要

Oral squamous cell carcinoma (OSCC) is the sixth most common malignancy which is a major cause for cancer morbidity and mortality worldwide. Early diagnosis and intervention improves the overall survival rate.The current study was done to evaluate the accuracy of salivary LDH as a potential biomarker for diagnosis of OSCC and to correlate the levels of salivary LDH with the histological differentiation of the tumour.Thirty patients visiting the outpatient department diagnosed clinically and histologically with OSCC were selected for the study with a control group of 20 patients. Unstimulated salivary samples collected from the selected patients were centrifuged and processed. Readings of enzyme activity in the salivary samples was established through auto analysis using International Federation of Clinical Chemistry (IFCC) method. Levels of the enzyme activity in both the control and the study group were compared and statistically analysed using student t-test. The three subgroups were also compared and statistically analysed.The results showed a mean value of 497.00 with a SD of 51.75 among the control group and a mean value of 1225.40 with a SD of 221.79 among the cases with a p-value of 0.0001 which was statistically significant. Furthermore, when the LDH values for the various grades of OSCC were compared, the mean values were 1049.07, 1309.50 and 1586.20 respectively, for well differentiated, moderately differentiated and poorly differentiated carcinoma.The p-value thus obtained revealed LDH values which were significantly higher in patients with OSCC and furthermore the levels significantly correlated with the histopathological grade of the tumour.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
cyy完成签到,获得积分10
1秒前
fengtj发布了新的文献求助10
1秒前
cccxxx完成签到,获得积分10
1秒前
1秒前
2秒前
zyj发布了新的文献求助10
2秒前
田田完成签到,获得积分10
3秒前
niu发布了新的文献求助30
3秒前
欧米伽发布了新的文献求助10
3秒前
yangyang完成签到,获得积分10
3秒前
3秒前
冰淇凌发布了新的文献求助10
3秒前
小雨发布了新的文献求助30
3秒前
11完成签到,获得积分10
3秒前
斯文败类应助athena采纳,获得10
4秒前
5秒前
5秒前
5秒前
mumu发布了新的文献求助10
5秒前
在水一方应助天成采纳,获得10
5秒前
彭于晏应助Wang采纳,获得10
5秒前
5秒前
6秒前
lpp_完成签到 ,获得积分10
6秒前
FashionBoy应助wxr采纳,获得10
6秒前
6秒前
骑龙猪猪完成签到,获得积分10
7秒前
bkagyin应助罗罗诺亚采纳,获得10
7秒前
在水一方应助孙博采纳,获得10
7秒前
哈基哈基哈基完成签到,获得积分10
7秒前
cccxxx发布了新的文献求助10
8秒前
大个应助伯纳乌与你采纳,获得10
8秒前
情怀应助wmbgmt采纳,获得10
8秒前
9秒前
不拼怎会赢完成签到,获得积分10
9秒前
老肥完成签到 ,获得积分10
10秒前
10秒前
fengtj完成签到,获得积分10
10秒前
10秒前
10秒前
高分求助中
Overcoming Stigma and Bias in Obesity Management 800
Malcolm Fraser : a biography 700
Signals, Systems, and Signal Processing 610
Materials selection in mechanical design 500
Bounds for Statistical Estimation in Semiparametric Models 500
Forced degradation and stability indicating LC method for Letrozole: A stress testing guide 500
Ideology and Meaning-Making under the Putin Regime 450
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6478602
求助须知:如何正确求助?哪些是违规求助? 8280115
关于积分的说明 17659941
捐赠科研通 5561094
什么是DOI,文献DOI怎么找? 2911191
邀请新用户注册赠送积分活动 1888194
关于科研通互助平台的介绍 1742021