Evidence map›Paper›PMID 39425746›Full record

ArticleCancer control : journal of the Moffitt Cancer Center

Prescription Opioid Use before and after Diagnosis of Cancer Among Older Cancer Survivors With Non-Cancer Chronic Pain Conditions (NCPCs): An Application of Group-Based Trajectory Modeling (GBTM).

Rudi Safarudin, Traci LeMasters, Salman Khan, Usha Sambamoorthi

Abstract read
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In one paragraph

Article in Cancer control : journal of the Moffitt Cancer Center. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Opioid prescription patterns in long-term disease-free cancer survivors: a retrospective analysis at a single NCI-designated comprehensive cancer center.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2025
    Observational
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

4 authors.

Rudi SafarudinDepartment of Pharmacy, Faculty of Mathematics and Natural Sciences, Tadulako University, Palu, Central Sulawesi, Indonesia.ORCID 0000-0003-4906-9212
Traci LeMastersDepartment of Pharmaceutical Systems and Policy, School of Pharmacy, West Virginia University, Morgantown, WV, USA.ORCID 0000-0002-6998-2650
Salman KhanDepartment of Internal Medicine, School of Medicine, University of Texas Southwestern Medical Center, Dallas, TX, USA.ORCID 0000-0001-5983-8965
Usha SambamoorthiDepartment of Pharmaceutical Systems and Policy, School of Pharmacy, West Virginia University, Morgantown, WV, USA.ORCID 0000-0001-8311-1360

Funding

AIM-AHEAD Coordinating Center - All Four CoresOT2OD032581 · OD · UNIVERSITY OF NORTH TEXAS HLTH SCI CTR · PI Paul Avillach, Bettina M. Beech · 2021 to 2026
$168.7M
NCI NIH HHS HHSN261201800009CNCI NIH HHS HHSN261201800009INCI NIH HHS HHSN261201800015CNCI NIH HHS HHSN261201800015INCI NIH HHS HHSN261201800032CNCI NIH HHS HHSN261201800032INIH HHS OT2 OD032581
6 · The paper itself

Abstract

backgroundPrescription opioids are essential in managing pain among adults with chronic pain conditions. However, persistent use over time can lead to negative health consequences. Identifying individuals with persistent use over time and their characteristics can inform clinical decision-making and aid in reducing the risk of abuse and overdose deaths.

objectiveThis study aims to examine trajectories of prescription opioid use over time and factors associated with these trajectories among older cancer survivors with any non-cancer pain conditions (NCPC).

methodsWe conducted a retrospective cohort study design with longitudinal data of older (age at cancer diagnosis ≥67 years) cancer (incident breast, colorectal, and prostate cancers, or non-Hodgkin lymphoma) survivors with any NCPC. Data were derived from the 2007-2015 linked Surveillance, Epidemiology, and End Results (SEER)-Medicare dataset (N = 35,071). Group-Based Trajectory Modeling (GBTM) was used to identify homogeneous subgroups (distinct trajectories) of individuals based on every 90-day prescription opioid use during pre-cancer diagnosis (t

resultsFour distinct trajectories of opioid use were identified: (1) increase-decrease use (6.1%); (2) short-term use after cancer diagnosis (40.6%); (3) low-use (41.0%); and (4) persistent use (12.3%). In the fully-adjusted multinomial logistic regression, the SDoH such as Non-Hispanic Black [adjusted odds ratios (AOR) = 1.69; 95%CI = 1.48, 1.93)] and rural residence (AOR = 1.49; 95%CI = 1.15, 1.94)], comorbid anxiety (AOR = 1.33; 95%CI = 1.18, 1.51), and medication use (NSAIDs - AOR = 1.20; 95%CI = 1.10, 1.30) were associated with membership in the persistent use group. Persistent use was less likely among those with higher fragmented care index (AOR = 0.95, 95%CI = 0.93, 0.97) and those living in counties with higher Medicare advantage penetration (AOR = 0.96; 95%CI = 0.95, 0.97).

conclusionsOne in eight older adults had persistent opioid use over time. The profile characteristics of this group were different from the other trajectory groups. Policies and programs to reduce chronic opioid use need to consider the intra- and inter-individual variability to reduce opioid-related morbidity and mortality.

Indexed as

Analgesics, OpioidCancer SurvivorsChronic PainAgedAged, 80 and overFemaleHumansLongitudinal StudiesMaleMedicareNeoplasmsRetrospective StudiesSEER ProgramUnited StatesAnalgesics, Opioidcancerchronic paingroup-based trajectory modelingopioidspersistent usetrajectory

Identifiers

PMID39425746
PMCPMC11526253

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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.