The CREST trial showed benefit driven by patients with carcinoma in situ (CIS), while the Potomac trial showed a lack of benefit in the same subgroup. This stark inconsistency demonstrates that subgroup analyses, even for stratified factors, can be unreliable and are a weak basis for regulatory decisions or label restrictions.

A patient's self-reported data can be incomplete or biased, as they may only report the "good measures." To get the full picture, companies must gather input from multiple sources, like caregivers and clinicians. Each perspective helps correct the others, creating a more accurate and holistic view of the patient's journey.

While regulators are open to using Patient-Reported Outcomes (PROs) for drug approval, the oncology community reflexively prioritizes survival data. This cultural bias sees PROs as "softer" endpoints, hindering the approval of drugs based on how patients feel and function.

The FDA receives raw and cleaned datasets from sponsors, not just summary reports. Their internal teams conduct independent analyses, which can lead to findings or data presentations in the official drug label that differ from or expand upon what's in the published paper.

To avoid stakeholders undermining research results later ('you only talked to 38 people'), proactively collaborate with them before the study to define the minimum standard of rigor they will accept. This alignment shifts the conversation from a post-mortem critique to a pre-launch agreement, disarming future objections.

The PCWG criteria are not consensus-based practice guidelines but are proposed frameworks for uniform data collection in trials. They are designed to be tested and validated (or disproven) by data, with the ultimate goal of qualifying biomarkers for drug approval.

To be effective, the patient's lived experience cannot remain a "soft narrative." It must be converted into hard data points—like reduced healthcare utilization for payers or influence on treatment pathways for clinicians—to become a decision-making tool they cannot ignore.

The influential "2+2 rule" on bone scans, which accounts for treatment "flare," wasn't an arbitrary threshold. It was proposed as a working hypothesis to be tested and validated through numerous clinical trials. This exemplifies the data-driven, iterative process behind the PCWG criteria.

The CREST trial's positive primary endpoint, assessed by investigators in an open-label setting, was rendered negative upon review by a blinded independent committee. This highlights the critical risk of confirmation bias and the immense weight regulators place on blinded data to determine a drug's true efficacy, especially when endpoints are subjective.