Evidence map›Paper›PMID 37308127›Full record

ArticleJournal of the National Comprehensive Cancer Network : JNCCN2023

Predicting All-Cause Mortality in Women With and Without Breast Cancer Using the Schonberg Index: A Women's Health Initiative Study.

Rebecca A Nelson, Enrique Soto-Perez-de-Celis, Rowan T Chlebowski, Mara Schonberg, Joanne Mortimer, Kathy Pan, Lifang Hou, Marian L Neuhouser, Kerryn W Reding, Nazmus Saquib and 4 more

Abstract read
In one paragraph

Article in Journal of the National Comprehensive Cancer Network : JNCCN, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Rebecca A NelsonCity of Hope National Medical Center, Duarte, California.
Enrique Soto-Perez-de-CelisDepartment of Geriatrics, National Institute of Medical Sciences and Nutrition Salvador Zubirán, Mexico City, Mexico.
Rowan T ChlebowskiThe Lundquist Institute, Torrance, California.
Mara SchonbergBeth Israel Deaconess Medical Cancer, Harvard Medical School, Boston, Massachusetts.
Joanne MortimerCity of Hope National Medical Center, Duarte, California.
Kathy PanKaiser Permanente, Bellflower, California.
Lifang HouNorthwestern University Feinberg School of Medicine, Evanston, Illinois.
Marian L NeuhouserFred Hutchinson Cancer Research Center, Seattle, Washington.
Kerryn W RedingUniversity of Washington, Seattle, Washington.
Nazmus SaquibSulaiman Al Rajhi College of Medicine, Al Bukairiyah, Saudi Arabia.
Jean Wactawski-WendeUniversity of Buffalo, Buffalo, New York.
Emily WolfsonBeth Israel Deaconess Medical Cancer, Harvard Medical School, Boston, Massachusetts.
Mina S SedrakCity of Hope National Medical Center, Duarte, California.
Laura KruperCity of Hope National Medical Center, Duarte, California.

Funding

Women's Health Initiative Clinical Coordinating CenterN01WH22110 · WH · FRED HUTCHINSON CANCER RESEARCH CENTER · PI PRENTICE, ROSS L · 2007 to 2010
$22.5M
A prediction model to simultaneously estimate personal risk of breast cancer and death from other causes in women aged 55 and olderR01CA242747 · NCI · BETH ISRAEL DEACONESS MEDICAL CENTER · PI SCHONBERG, MARA A · 2020 to 2023
$2.3M
WOMENS HEALTH INITIATIVE-N01WH22110N01WH022110 · WH · FRED HUTCHINSON CANCER RESEARCH CENTER · PI ROSS, PRENTICE · 1992 to 2006
$1.2M
Research and mentoring program in shared decision making in the care of older adultsK24AG071906 · NIA · BETH ISRAEL DEACONESS MEDICAL CENTER · PI SCHONBERG, MARA A · 2021 to 2025
$946k
NCI NIH HHS R01 CA242747NIA NIH HHS K24 AG071906WHI NIH HHS N01WH22110
6 · The paper itself

Abstract

backgroundWhen treating older women with breast cancer, life expectancy is an important consideration. ASCO recommends calculating 10-year mortality probabilities to inform treatment decisions. One useful tool is the Schonberg index, which predicts risk-based all-cause 10-year mortality. We investigated the use of this index in women aged ≥65 years with breast cancer in the Women's Health Initiative (WHI).

methodsWe calculated 10-year mortality risk scores for 2,549 WHI participants with breast cancer ("cases") and 2,549 age-matched breast cancer-free participants ("controls") using Schonberg index risk scoring. Risk scores were grouped into quintiles for comparisons. Risk-stratified observed mortality rates and 95% confidence intervals were compared across cases and controls. Observed 10-year mortality rates in cases and controls were also compared with Schonberg index-based predicted 10-year mortality rates.

resultsCompared with controls, cases were more often white (P=.005), had higher income and education levels (P<.001 for both), more often lived with their husband/partner (P<.001), scored higher on subjective health/happiness (P<.001), and needed less assistance in activities of daily living (P<.001). Participants with breast cancer had similar risk-stratified 10-year mortality rates compared with controls (34% vs 33%, respectively). Stratified results showed that cases had slightly higher mortality rates than controls in the lowest risk quintile and lower mortality rates in the 2 highest risk quintiles. Observed mortality rates in cases and controls were similar to Schonberg index-predicted mortality, with model c-indexes of 0.71 and 0.76, respectively.

conclusionsAmong women aged ≥65 years with incident breast cancer, the Schonberg index-based risk-stratified 10-year mortality rates were similar to those in women without breast cancer, demonstrating a similar performance of the index among both populations. Along with other health measures, prognostic indexes can help predict survival among older women with breast cancer and support geriatric oncology guidelines that promote using life expectancy calculation tools for shared decision-making.

Indexed as

Activities of Daily LivingBreast NeoplasmsAgedBreastDecision Making, SharedFemaleHumansWomen's Healthbreast cancergeriatricmortalityrisk index

Identifiers

PMID37308127
PMCPMC12833738

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.