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Age-related differences in cancer relative survival in the US: a SEER-18 analysis.

Diana R WithrowBrian D NicholsonEva Ja MorrisMelisa L WongSophie Pilleron
Published in: International journal of cancer (2023)
Cancer survival has improved since the 1990s, but to different extents across age groups, with a disadvantage for older adults. We aimed to quantify age-related differences in relative survival (RS - one-year, and one-year conditioning on surviving one year) for 10 common cancer types by stage at diagnosis. We used data from 18 United States Surveillance Epidemiology and End Results cancer registries and included cancers diagnosed in 2012-2016 followed until December 31, 2017. We estimated absolute differences in RS between the 50-64 age group and the 75-84 age group. The smallest differences were observed for prostate and breast cancers (1.8%-points [95% confidence interval (CI):1.5-2.1] and 1.9%-points [95%CI: 1.5-2.3], respectively). The largest was for ovarian cancer (27%-points, 95%CI: 24-29). For other cancers, differences ranged between 7 (95%CI: 5-9, esophagus) and 18%-points (95%CI: 17-19, pancreas). Except for pancreatic cancer, cancer type and stage combinations with very high (>95%) or very low (<40%) one-year RS tended to have smaller age-related differences in survival than those with mid-range prognoses. Age-related differences in one-year survival conditioning on having survived one-year were small for most cancer and stage combinations. The broad variation in survival differences by age across cancer types and stages, especially in the first year, age-related differences in survival are likely influenced by amenability to treatment. Future work to measure the extent of age-related differences that are avoidable, and identify how to narrow the survival gap, may have most benefit by prioritizing cancers with relatively large age-related differences in survival (e.g., stomach, esophagus, liver and pancreas).
Keyphrases
  • papillary thyroid
  • squamous cell
  • free survival
  • prostate cancer
  • childhood cancer
  • public health
  • squamous cell carcinoma
  • risk factors
  • machine learning
  • electronic health record