AOA dx
1 in 78 women will be diagnosed with ovarian cancer in
their lifetime
By 2035...
new cases will increase by 55%
and
deaths will increase by 67%
HOWEVER
If 75%* of ovarian cancer cases
could be detected at stage I or II,
the number of deaths from this disease would be
reduced by half.
* 75% versus the 25% of ovarian cancer cases which are presently detected at stage I or II.
Why early diagnosis matters
Ovarian cancer is the fifth leading cause of cancer-related deaths in women 35-74.
Ovarian Cancer is no longer a silent disease.
94% of women experience symptoms starting from Stage 1
Only about 20% of all cases are found early (stage I or II).
30% survival rate in late stage with a 94% recurrence.
Five year survival rate
The average cost of care for women with ovarian cancer in the first year after surgery is approximately $100,000.
Ovarian cancer is the second most expensive cancer to treat in women, second only to brain.
Early diagnosis of ovarian cancer is expected to half the number of deaths and significantly reduce the costs of treatment and recurrence.
Vague symptoms and current diagnostic methods lack specificity and sensitivity in stages I and II.
By the time a diagnosis of ovarian cancer is considered, the cancer has usually spread beyond the ovaries.
AOA is developing a technology that has altered the way we approach early-stage diagnosis.
Akrivis GD
TM
A liquid biopsy test that shows excellent results in the early diagnosis of ovarian cancer through analysis of tumor marker gangliosides.
POWERFUL TECHNOLOGY
Tumor glycolipids: unexploited markers for diagnosis
Preferred biomarker target:
Originated in cancer
>80% of patients express target at millions/tumor cell
Stable non-mutating targets
Present throughout the cancer lifecycle and in relapse
Originates in tumor tissue
The preliminary results demonstrate high sensitivity and specificity across all cancer stages in both premenopausal and postmenopausal women.
Early diagnosis increases survival rates.
The early data is currently being cross validated in a large multi-center statistically significant cohort.
