The impact of cancer survivors’ extra risk of noncancer mortality on net survival estimation - Report - MDSpire

The impact of cancer survivors’ extra risk of noncancer mortality on net survival estimation

  • By

  • Laura Botta

  • Riccardo Capocaccia

  • Alice Bernasconi

  • Silvia Rossi

  • Jaume Galceran

  • Luigino Dal Maso

  • Come Lepage

  • Florence Molinié

  • Anne-Marie Bouvier

  • Rafael Marcos-Gragera

  • Claudia Vener

  • Marcela Guevara

  • Deirdre Murray

  • Rosalia Ragusa

  • Gemma Gatta

  • Valerie Jooste

  • the EUROCARE-6 WG

  • M Hackl

  • E Van Eycken

  • N Van Damme

  • Z Valerianova

  • M Sekerija

  • V Scoutellas

  • A Demetriou

  • L Dušek

  • D Krejici

  • H Storm

  • M Mägi

  • K Innos

  • J Pitkäniemi

  • M Velten

  • X Troussard

  • A M Bouvier

  • V Jooste

  • A V Guizard

  • G Launoy

  • S Dabakuyo Yonli

  • M Maynadié

  • A S Woronoff

  • J B Nousbaum

  • G Coureau

  • A Monnereau

  • I Baldi

  • K Hammas

  • B Tretarre

  • M Colonna

  • S Plouvier

  • T D'Almeida

  • F Molinié

  • A Cowppli-Bony

  • S Bara

  • A Debreuve

  • G Defossez

  • B Lapôtre-Ledoux

  • P Grosclaude

  • L Daubisse-Marliac

  • S Luttmann

  • A Eberle

  • R Stabenow

  • A Nennecke

  • J Kieschke

  • S Zeissig

  • B Holleczek

  • A Katalinic

  • H Birgisson

  • D Murray

  • P M Walsh

  • G Mazzoleni

  • F Vittadello

  • F Cuccaro

  • R Galasso

  • G Sampietro

  • S Rosso

  • C Gasparotti

  • G Maifredi

  • M Ferrante

  • R Ragusa

  • A Sutera Sardo

  • M L Gambino

  • M Lanzoni

  • P Ballotari

  • E Giacomazzi

  • S Ferretti

  • A Caldarella

  • G Manneschi

  • G Gatta

  • M Sant

  • P Baili

  • F Berrino

  • L Botta

  • A Trama

  • R Lillini

  • A Bernasconi

  • S Bonfarnuzzo

  • C Vener

  • F Didonè

  • P Lasalvia

  • L Buratti

  • G Tagliabue

  • D Serraino

  • L Dal Maso

  • R Capocaccia

  • R De Angelis

  • E Demuru

  • F Cerza

  • F Di Mari

  • C Di Benedetto

  • S Rossi

  • M Santaquilani

  • S Venanzi

  • M Tallon

  • L Boni

  • S Iacovacci

  • V Gennaro

  • A G Russo

  • F Gervasi

  • G Spagnoli

  • L Cavalieri d'Oro

  • M Fusco

  • M F Vitale

  • P Pinna

  • W Mazzucco

  • M Michiara

  • G Chiranda

  • G Cascone

  • M C Giurdanella

  • L Mangone

  • F Falcini

  • R Cavallo

  • D Piras

  • A Madeddu

  • F Bella

  • A C Fanetti

  • S Minerba

  • G Candela

  • T Scuderi

  • R V Rizzello

  • F Stracci

  • M Zorzi

  • S Guzzinati

  • A Brustolin

  • S Pildava

  • I Vincerzevskiene

  • M Azzopardi

  • T B Johannesen

  • J Didkowska

  • U Wojciechowska

  • M Bielska-Lasota

  • A Pais

  • M J Bento

  • C Alves-Rodrigues

  • A Lourenço

  • A Mayer

  • C Safaei Diba

  • V Zadnik

  • T Zagar

  • C Sánchez-Contador Escudero

  • P Franch Sureda

  • A Lopez de Munain

  • M De-La-Cruz

  • M D Rojas

  • A Aleman

  • A Vizcaino

  • R Marcos-Gragera

  • A Sanvisens

  • M J Sanchez

  • M D Chirlaque Lopez

  • A Sanchez-Gil

  • M Guevara

  • E Ardanaz

  • J Galceran

  • M Carulla

  • Y Bergeron

  • E Rapiti

  • R Schaffar

  • S Mohsen Mousavi

  • P Went

  • S Mohsen Mousavi

  • M Blum

  • A Bordoni

  • O Visser

  • S Siesling

  • S Stevens

  • J Broggio

  • D Bennett

  • A Gavin

  • D Morrison

  • D W Huws

  • August 19, 2025

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Impact of Increased Noncancer Mortality Risk on Net Survival Estimates in Cancer Survivors

Overview

This study evaluates how an increased risk of noncancer death among cancer survivors affects the accuracy of net survival (NS) estimates when using relative survival (RS) methods. Findings indicate that RS underestimates NS particularly in older patients, longer follow-up times, and cancers with higher NS, with variability by cancer type and patient demographics.

Background

Net survival (NS) estimates the probability of surviving cancer in the hypothetical absence of other causes of death and is commonly derived using relative survival (RS) methods that compare cancer patient survival to that of the general population. These methods assume equal risk of noncancer death between cancer patients and the general population. However, cancer survivors often have an elevated risk of dying from other causes due to treatment effects or comorbidities, which can bias NS estimates. Understanding this bias is critical for accurate cancer survival comparisons and clinical decision-making.

Data Highlights

Cancer TypeDifference Between RS and NS (%)Patient GroupTime Since Diagnosis
Head and Neck4%Young Female Patients5 years
Head and Neck32%Older Patients5 years
Colorectal<7%All Ages and SexesAll Times
Breast<5%All Except Older PatientsAll Times
Breast>5%Older PatientsAfter 5 years

Key Findings

  • RS underestimates NS when cancer survivors have a relative risk (RR) of noncancer death greater than 1 compared to the general population.
  • The discrepancy between RS and NS increases with longer time since diagnosis, older age at diagnosis, and higher NS values.
  • For head and neck cancer, differences ranged from 4% in young females to 32% in older patients at 5 years post-diagnosis.
  • Colorectal cancer showed smaller differences (<7%) across all ages, sexes, and follow-up times.
  • Breast cancer differences were generally under 5%, except in older patients after 5 years where differences increased.
  • Assuming equal noncancer mortality risk between patients and the general population can bias NS estimates, impacting interpretation of cancer-specific survival.

Clinical Implications

Clinicians and epidemiologists should be cautious when interpreting net survival estimates derived from relative survival methods, especially in older cancer survivors and those with longer follow-up periods. Adjusting for increased noncancer mortality risk in cancer survivors may provide more accurate survival estimates, which are essential for patient counseling, surveillance planning, and resource allocation. Awareness of these biases can improve the clinical relevance of survival statistics.

Conclusion

The study highlights that increased noncancer mortality risk in cancer survivors leads to underestimation of net survival when using relative survival methods. Recognizing and adjusting for this bias is important for accurate assessment of cancer-specific survival and informed clinical decision-making.

References

  1. EUROCARE-6 Study -- Cancer Survival Estimates and Methodology
  2. Pohar Perme et al. -- Net Survival Estimation Methods
  3. Recent Modeling Studies on Noncancer Mortality Risk in Cancer Survivors

Original Source(s)

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