News & Comment

Cancer screening is an effective strategy for reducing cancer mortality, but in resource-constrained settings the key challenge is not simply whether screening works but how its implementation should be prioritized. We propose a framework for prioritizing cancer screening under resource constraints, summarized in three ‘not all’ principles: not all cancers are suitable for screening; not all individuals need screening; and not all high-performance technologies are appropriate for population screening.

This Comment describes the clinical significance of the Mammography Screening with Artificial Intelligence (MASAI) trial, which is, to the best of our knowledge, the first randomized trial of artificial intelligence-supported mammography interpretation to examine interval cancer as an outcome. This trial used artificial intelligence to assign single-reading versus double-reading of mammograms and found that this approach does not increase interval cancers in the Swedish population.

Although oncology advances stem from clinical research, <5% of global cancer trials actively recruit patients in Latin America. Herein, I discuss why expanding inclusive trial designs and fostering multisector partnerships are essential to reduce disparities and improve the role of Latin America in global oncology research. I present examples such as the recent regulatory reforms in Brazil that aim to accelerate study approvals, as well as collaborative initiatives between local and international research groups to further strengthen clinical trial capacity.

Artificial intelligence (AI) excels at rapid data synthesis and pattern recognition, yet the practice of oncology demands nuanced clinical judgement, ethical reasoning and authentic empathy — qualities only humans can provide. The future of cancer care lies in synergy: AI augmenting human expertise, not replacing it. Excellence emerges when computational power meets clinical wisdom.