You need to assume something about how the failure times are distributed to answer your question. If we prove, for example, that only 1% of parts fail by 50 hours, how do we know what that means at 132.5 hours? We need to project reliability at one time to reliability at another, so we need to assume a life distribution, as Miner correctly stated above.

The basic concept here is that some failure modes get worse with age (to varying degrees), some actually get better with age (such as manufacturing defects), and by assuming a Weibull distribution and a slope of say 2, we're basically saying "I know it will get worse at this rate." That allows you to make the connection between, let's say, 99% reliability at 50 hours and 95% reliability at 132.5 hours (which would correspond to a Weibull slope of 1.7).

Here's a more thorough explanation of the different mathematical methodologies of reliability test design, with explanations as to why you need to assume the life distribution in this case.

Full disclosure: I work for the company that produces this wiki (ReliaWiki) and the software referenced in it (Weibull++).