Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 4 de 4
Filtrar
1.
JAMA Otolaryngol Head Neck Surg ; 148(11): 1059-1067, 2022 11 01.
Artigo em Inglês | MEDLINE | ID: mdl-36173618

RESUMO

Importance: In clinical practice, assessment schedules are often arbitrarily determined after definitive treatment of head and neck cancer (HNC), producing heterogeneous and inconsistent surveillance plans. Objective: To establish an optimal assessment schedule for patients with definitively treated locally advanced HNC, stratified by the primary subsite and HPV status, using a parametric model of standardized event-free survival curves. Design, Setting, and Participants: This was a retrospective study including 2 tertiary referral hospitals and a total of 673 patients with definitive locoregional treatment of locally advanced HNC (227 patients with nasopharyngeal cancer [NPC]; 237 patients with human papillomavirus-positive oropharyngeal cancer [HPV+ OPC]; 47 patients with HPV-negative [HPV-] OPC; 65 patients with hypopharyngeal cancer [HPC]; and 97 patients with laryngeal cancer [LC]). Patients had received primary treatment in 2008 through 2019. The median (range) follow-up duration was 57.8 (6.4-158.1) months. Data analyses were performed from April to October 2021. Main Outcomes and Measures: Tumor recurrence and secondary malignant neoplasms. Event-free survival was defined as the period from the end of treatment to occurrence of any event. Event-free survival curves were estimated using a piecewise exponential model and divided into 3 phases of regular follow-up. A 5% event rate criterion determined optimal follow-up time point and interval. Results: The median (range) age of the 673 patients at HNC diagnosis was 58 (15-83) years; 555 (82.5%) were men; race and ethnicity were not considered. The event rates of NPC, HPV+ OPC, HPV- OPC, HPC, and LC were 18.9% (43 of 227), 14.8% (35 of 237), 36.2% (17 of 47), 44.6% (29 of 65), and 30.9% (30 of 97), respectively. Parametric modeling demonstrated optimal follow-up intervals for HPC, LC, and NPC, respectively, every 2.1, 3.2, and 6.1 months; 3.7, 5.6, and 10.8 months; and 9.1, 13.8, and 26.5 months until 16.5, 16.5 to 25.0, and 25.0 to 99.0 months posttreatment (open follow-up thereafter). For HPV- OPC, assessment was recommended every 2.7, 4.8, and 11.8 months until 16.5, 16.5 to 25.0, and 25 to 99 months posttreatment, respectively. In contrast, HPV+ OPC optimal intervals were every 7.7, 13.7, and 33.7 months until 16.5, 16.5 to 25.0, and 25 to 99 months posttreatment, respectively. Five, 4, 12, 15, and 10 follow-up visits were recommended for NPC, HPV+ OPC, HPV- OPC, HPC, and LC, respectively. Conclusions and Relevance: This retrospective cohort study using parametric modeling suggests that the HNC assessment schedules should be patient tailored and evidence based to consider primary subsites and HPV status. Given limited health care resources and rising detection rates and costs of HNC, the guidelines offered by these findings could benefit patients and health systems and aid in developing future consensus guidelines.


Assuntos
Neoplasias de Cabeça e Pescoço , Neoplasias Hipofaríngeas , Neoplasias Laríngeas , Neoplasias Nasofaríngeas , Neoplasias Orofaríngeas , Infecções por Papillomavirus , Masculino , Humanos , Pessoa de Meia-Idade , Idoso , Idoso de 80 Anos ou mais , Feminino , Estudos Retrospectivos , Infecções por Papillomavirus/complicações , Infecções por Papillomavirus/terapia , Infecções por Papillomavirus/diagnóstico , Neoplasias Nasofaríngeas/complicações , Intervalo Livre de Progressão , Recidiva Local de Neoplasia/terapia , Recidiva Local de Neoplasia/complicações , Neoplasias Orofaríngeas/terapia , Neoplasias de Cabeça e Pescoço/terapia , Neoplasias de Cabeça e Pescoço/complicações , Neoplasias Hipofaríngeas/complicações , Neoplasias Laríngeas/terapia , Neoplasias Laríngeas/complicações , Sobreviventes
2.
Neurooncol Adv ; 3(1): vdab069, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34286277

RESUMO

BACKGROUND: There have been no evidence-based guidelines on the optimal schedule for the radiological assessment of 1p/19q-codeleted glioma. This study aimed to recommend an appropriate radiological evaluation schedule for 1p/19q-codeleted glioma during the surveillance period through parametric modeling of the progression-free survival (PFS) curve. METHODS: A total of 234 patients with 1p/19q-codeleted glioma (137 grade II and 97 grade III) who completed regular treatment were retrospectively reviewed. The patients were stratified into each layered progression risk group by recursive partitioning analysis. A piecewise exponential model was used to standardize the PFS curves. The cutoff value of the progression rate among the remaining progression-free patients was set to 10% at each scan. RESULTS: Progression risk stratification resulted in 3 groups. The optimal magnetic resonance imaging (MRI) interval for patients without a residual tumor was every 91.2 weeks until 720 weeks after the end of regular treatment following the latent period for 15 weeks. For patients with a residual tumor after the completion of adjuvant radiotherapy followed by chemotherapy, the optimal MRI interval was every 37.5 weeks until week 90 and every 132.8 weeks until week 361, while it was every 33.6 weeks until week 210 and every 14.4 weeks until week 495 for patients with a residual tumor after surgery only or surgery followed by radiotherapy only. CONCLUSIONS: The optimal radiological follow-up schedule for each progression risk stratification of 1p/19q-codeleted glioma can be established from the parametric modeling of PFS.

3.
Neuro Oncol ; 23(5): 837-847, 2021 05 05.
Artigo em Inglês | MEDLINE | ID: mdl-33130858

RESUMO

BACKGROUND: An optimal radiological surveillance plan is crucial for high-grade glioma (HGG) patients, which is determined arbitrarily in daily clinical practice. We propose the radiological assessment schedule using a parametric model of standardized progression-free survival (PFS) curves. METHODS: A total of 277 HGG patients (178 glioblastoma [GBM] and 99 anaplastic astrocytoma [AA]) from a single institute who completed the standard treatment protocol were enrolled in this cohort study and retrospectively analyzed. The patients were stratified into each layered risk group by genetic signatures and residual mass or through recursive partitioning analysis. PFS curves were estimated using the piecewise exponential survival model. The criterion of a 10% progression rate among the remaining patients at each observation period was used to determine the optimal radiological assessment time point. RESULTS: The optimal follow-up intervals for MRI evaluations of isocitrate dehydrogenase (IDH) wild-type GBM was every 7.4 weeks until 120 weeks after the end of standard treatment, followed by a 22-week inflection period and every 27.6 weeks thereafter. For the IDH mutated GBM, scans every 13.2 weeks until 151 weeks are recommended. The optimal follow-up intervals were every 22.8 weeks for IDH wild-type AA, and 41.2 weeks for IDH mutated AA until 241 weeks. Tailored radiological assessment schedules were suggested for each layered risk group of the GBM and the AA patients. CONCLUSIONS: The optimal schedule of radiological assessments for each layered risk group of patients with HGG could be determined from the parametric model of PFS.


Assuntos
Neoplasias Encefálicas , Glioma , Neoplasias Encefálicas/diagnóstico por imagem , Neoplasias Encefálicas/genética , Estudos de Coortes , Glioma/diagnóstico por imagem , Glioma/genética , Humanos , Isocitrato Desidrogenase/genética , Estudos Retrospectivos
4.
Lifetime Data Anal ; 17(2): 302-20, 2011 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-20635203

RESUMO

We propose a Bayesian approach for estimating the hazard functions under the constraint of a monotone hazard ratio. We construct a model for the monotone hazard ratio utilizing the Cox's proportional hazards model with a monotone time-dependent coefficient. To reduce computational complexity, we use a signed gamma process prior for the time-dependent coefficient and the Bayesian bootstrap prior for the baseline hazard function. We develop an efficient MCMC algorithm and illustrate the proposed method on simulated and real data sets.


Assuntos
Algoritmos , Teorema de Bayes , Modelos de Riscos Proporcionais , Simulação por Computador , Feminino , Humanos , Leucemia/tratamento farmacológico , Cadeias de Markov , Mercaptopurina/uso terapêutico , Método de Monte Carlo , Neoplasias Ovarianas/tratamento farmacológico , Processos Estocásticos
SELEÇÃO DE REFERÊNCIAS
DETALHE DA PESQUISA