Which statement describes how alpha-spending works in controlling Type I error during interim analyses?

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Alpha-spending controls Type I error when a trial is examined at interim times by pre-allocating the total alpha across these looks. The idea is to prevent the cumulative chance of a false-positive from exceeding the pre-specified level. A spending function defines how much alpha is "spent" at each interim and the final analysis, ensuring the total spent across all looks equals the overall alpha (for example, 0.05). Early looks may use stringent boundaries, with more lenient thresholds allowed later, depending on the chosen method (like O'Brien-Fleming or Pocock). This keeps the overall Type I error rate at the planned level despite multiple analyses. The other choices don't fit: alpha is not simply increased after each look; it’s fixed in total and allocated; alpha-spending does not remove the need for a primary endpoint; and it does not rely on post-hoc analyses to confirm efficacy.