ABSTRACT
Background
Time from surgery to initiation of postoperative radiation therapy (PORT) of less than 6 weeks was recently instituted as the first quality metric within head and neck cancer care.
Methods
We performed a retrospective single institution cohort study to investigate predictors of PORT delay and the impact of PORT delay on survival.
Results
PORT delay rate was 73.2%, with a median time to treatment initiation of 51 days. Outside radiation facility treatment was independently associated with increased likelihood of PORT delay (OR 1.94, 95% CI 1.03–3.74, p = 0.043). PORT delay and location of radiation treatment did not impact OS or PFS.
Conclusions
In this single institution study, most patients experienced PORT delay. Patients that were treated at outside radiation facilities were more likely to experience delay. However, PORT delay did not result in statistically significant difference in OS and PFS which contrasts with the current literature.
Keywords: head and neck cancer, OS, PFS, PORT, postoperative radiation, TPT
1. Introduction
Head and neck cancer (HNC) management often involves surgical resection as the primary treatment modality [1]. Adjuvant radiation therapy is commonly administered for malignancies with high‐risk characteristics, which has contributed to improved outcomes in this patient population [2]. Timely initiation of postoperative radiation therapy (PORT) is crucial, as several studies have demonstrated the negative impact of delays in PORT on patient survival and outcomes [3, 4].A delay in initiating PORT beyond 6 weeks, or 42 days, following surgery has been associated with poorer locoregional control and overall survival (OS) [3, 4, 5]. Recognizing this, in 2022 the Commission on Cancer (CoC) and the American Head and Neck Society (AHNS) implemented a quality metric recommending that the time to initiation of PORT should be less than 6 weeks for surgically managed HNC patients.
Studies have suggested that radiation at an outside hospital can cause fragmentation of care and delay time to PORT [6, 7]. Additionally, PORT delay has been found to be the primary driver of treatment package time (TPT), impacting patient survival independent of diagnosis‐to‐surgery time and total radiation therapy duration [8]. Since the introduction of the 2022 CoC and AHNS quality metric, there has been a concerted effort in numerous studies to minimize the time to PORT initiation [5] in pursuit of enhancing survival outcomes, but it remains an understudied problem. While studies [9, 10] have found improved outcomes at higher‐volume centers compared to lower volume centers and literature has investigated survival outcomes at academic centers [11, 12], there is little literature on institutional versus outside radiation facility treatment [6, 7, 13]. Additionally, a divergence exists in literature regarding the association between PORT delay and patient outcomes. While some studies maintain ambiguity on this association stating that delay in PORT and patient outcomes is complex but ultimately does not affect survival [14], others demonstrate unequivocal adverse outcomes for PORT delay [4, 5].
Amidst the ambivalence in the existing literature, the current quality metric serves as a national call‐to‐action. While studies have investigated fragmentation of care, PORT delay, and survival differences separately, we hope to investigate the three factors concurrently. In this retrospective study, we seek to explore the impact of PORT facility location and PORT delay on survival. This investigation is crucial for informing potential interventions to reduce PORT delay and improve overall outcomes for surgically managed HNC patients.
2. Materials and Methods
We conducted a retrospective chart review of patients with HNC who underwent definitive surgical resection and received adjuvant PORT over 3 years, from January 1, 2018, through December 31, 2020. All patients underwent surgery at Vanderbilt University Medical Center (VUMC) and received adjuvant radiation therapy at either VUMC or an outside radiation facility. Patients with an unknown primary were excluded from analysis.
Patient, oncologic, and treatment characteristics were systematically documented. Notably, demographic details such as patient home address and radiation treatment facility address were recorded. The shortest driving distance between these locations was determined using publicly available Google Maps [14]. Additional recorded variables included patient race, employment status, insurance status, oncologic subsite, clinical, postoperative complications (both medical and surgical) and pathologic tumor, node, metastasis (TNM) staging. TNM staging was determined according to the American Joint Committee on Cancer staging of HNC eighth edition [15]. Key dates including diagnosis, surgery, radiation oncology referral, initiation of PORT, and conclusion of PORT were recorded. Delay in PORT was defined as greater than 42 days between surgery and the initiation of radiation treatment. Total treatment time was calculated as days from surgical resection to completion of PORT. Multivariable logistic regression was conducted to identify independent predictors of PORT delay. Factors included in multivariate models included all covariates that were different between those experiencing PORT delay and not experiencing PORT delay with an α < 0.20.
Log‐rank analyses were performed to assess factors associated with OS and progression‐free survival (PFS). The date of the last follow‐up with otolaryngology, radiation oncology, or medical oncology, was used to evaluate survival outcomes including disease status, recurrence, site of recurrence, and other specific recurrence details. Disease status was categorized as no evidence of disease (NED), alive with disease, deceased due to the disease, deceased due to other causes, and deceased (unknown etiology). The site of recurrence was classified as local, regional/lymph nodes, or distant metastases. Cox regression analysis was conducted to assess the independent impact of PORT delay on survival outcomes while adjusting for covariates including age, race, T‐stage, N‐stage, anatomic subsite, PORT delay, and the location of radiation therapy (outside facility vs. institutional). All analysis was conducted in R. Studio (R. RStudio, PBC, Boston, MA, http://www.rstudio.com/).
3. Results
3.1. Patient and Clinical Characteristics
We identified 236 HNC patients who received primary surgery and adjuvant radiation therapy between 2018 and 2020. Most patients were white (87%), male (75%), and had private insurance (53%). Sociodemographic factors are further detailed in Table 1, stratified by PORT delay. The most common tumor subsites included oral cavity (51%), oropharynx (10%), and hypopharynx/larynx (14%). Most patients received adjuvant radiation therapy with concurrent chemotherapy (62%). Most patients (53%) received PORT at VUMC where the definitive surgical resection was performed. Tumor and treatment characteristics are further detailed in Table 2.
TABLE 1.
Patient sociodemographic characteristics stratified by whether they received a PORT delay.
| Characteristics | No delay, N = 62 a | Delay, N = 174 a | p b |
|---|---|---|---|
| Age | 64 (56, 69) | 62 (54, 71) | 0.8 |
| Gender (female) | 16 (26%) | 43 (25%) | > 0.9 |
| Race | 0.2 | ||
| White | 54 (87%) | 155 (89%) | |
| Black | 4 (6.5%) | 16 (9.2%) | |
| Asian | 3 (4.8%) | 3 (1.7%) | |
| Other | 1 (1.6%) | 0 (0%) | |
| Ethnicity (Hispanic, yes) | 1 (1.6%) | 1 (0.6%) | 0.5 |
| Employment | 0.2 | ||
| Full‐time paid | 13 (21%) | 43 (25%) | |
| Part‐time paid | 1 (1.6%) | 1 (0.6%) | |
| Unemployed | 0 (0%) | 14 (8.0%) | |
| Disability | 7 (11%) | 16 (9.2%) | |
| Retired | 17 (27%) | 44 (25%) | |
| Other | 1 (1.6%) | 1 (0.6%) | |
| Unknown | 23 (37%) | 55 (32%) | |
| Insurance | 0.01 | ||
| Private | 33 (53%) | 94 (54%) | |
| Medicare | 24 (39%) | 60 (34%) | |
| Medicaid | 1 (1.6%) | 2 (1.1%) | |
| Other | 1 (1.6%) | 18 (10%) | |
| Unknown | 3 (4.8%) | 0 (0%) |
Note: Factors from this table that differed significantly with an α < 0.10 were included in multivariable models.
Median (IQR); n (%).
Wilcoxon's rank‐sum test; Fisher's exact test; Pearson's chi‐squared test.
TABLE 2.
Tumor characteristics and treatment characteristics stratified by whether the patient experienced a delay in PORT.
| Characteristics | No delay, N = 62 a | Delay, N = 174 a | p b |
|---|---|---|---|
| Cancer subsite | 0.4 | ||
| Oral cavity | 32 (52%) | 91 (52%) | |
| Oropharynx | 6 (9.7%) | 19 (11%) | |
| Hypopharynx | 0 (0%) | 2 (1.1%) | |
| Larynx | 8 (13%) | 23 (13%) | |
| Paranasal sinuses | 3 (4.8%) | 5 (2.9%) | |
| Nasal cavity | 6 (9.7%) | 4 (2.3%) | |
| Salivary | 2 (3.2%) | 8 (4.6%) | |
| Skin/scalp | 5 (8.1%) | 22 (13%) | |
| Histology | 0.4 | ||
| p16+ SCC mucosa | 7 (11%) | 13 (7.6%) | |
| p16− SCC mucosa | 42 (68%) | 119 (68%) | |
| SCC skin | 2 (3.2%) | 16 (9.2%) | |
| BCC skin | 0 (0%) | 1 (0.6%) | |
| Adenoid cystic carcinoma | 3 (4.8%) | 5 (2.9%) | |
| Mucoepidermoid cancer | 1 (1.6%) | 0 (0%) | |
| Other salivary cancer | 1 (1.6%) | 7 (4.1%) | |
| Other c | 6 (9.7%) | 13 (7.6%) | |
| T‐stage | 0.008 | ||
| 1 | 12 (19%) | 9 (5.2%) | |
| 2 | 9 (15%) | 38 (22%) | |
| 3 | 15 (24%) | 44 (25%) | |
| 4 | 26 (42%) | 83 (48%) | |
| N‐stage | 0.2 | ||
| 0 | 32 (52%) | 68 (39%) | |
| 1 | 8 (13%) | 20 (11%) | |
| 2/2a/2b/2c | 12 (19%) | 37 (21%) | |
| 3/3a/3b | 10 (16%) | 49 (28%) | |
| Complications | 12 (19%) | 55 (32%) | 0.066 |
| Treatment at home institution | 40 (65%) | 87 (50%) | 0.049 |
| Distance to radiation facility | 21 (10, 39) | 27 (11, 52) | 0.15 |
| PORT or CRT | 0.2 | ||
| PORT only | 17 (27%) | 68 (39%) | |
| CRT | 44 (71%) | 104 (60%) | |
| Unknown CRT d | 1 (1.6%) | 2 (1.1%) |
Note: Factors from this table that differed significantly with an α < 0.25 were included in multivariable models.
n (%); Median (IQR).
Fisher's exact test; Pearson's chi‐squared test; Wilcoxon's rank–sum test.
Other tumor types included adeno/adenosquamous carcinoma, myoepithelial carcinoma, neuroendocrine tumors, lymphoma, melanoma, neuroblastoma, spindle cell carcinoma, synovial sarcoma, Merkel cell carcinoma.
Unknown CRT patients were confirmed to receive PORT, but unclear whether they received chemotherapy.
3.2. Rate of PORT Delay and Clinical Timeline
The rate of PORT delay, defined as the initiation of radiation > 42 days after surgery, was 73%. The median delay per phase of case is shown in Figure 1 (figure medians are different due to exclusion of some missing radiation oncology referral data). For patients who received radiation therapy at VUMC, the surgery to PORT interval was 50 days (IQR 41–63 days). For those treated at an outside facility, the PORT interval was 56 days (IQR 44–73, p = 0.015). For patients with outside facility treatment, while surgery to radiation oncology referral is 1 day shorter than for VUMC radiation treatment patients, the diagnosis to surgery and radiation referral to radiation treatment intervals are several days longer, at 3 and 5 days, respectively. Total treatment time, referred to as TPT in some studies [8], for patients without PORT delay was 84 days and with delay was 104 days (p < 0.001).
FIGURE 1.
Clinical timeline—median delay per phase of case. Clinical timeline intervals for patients treated at VUMC (reference facility) versus outside facility: Diagnosis‐to‐surgery, surgery to radiation oncology referral, radiation oncology referral to radiation initiation.
3.3. Impact of Radiation Treatment Facility Location on PORT Delay
Radiation treatment at an outside facility had a higher rate of delay (80% vs. 69%, p = 0.049). Additionally, there was a trend toward PORT delay patients living further from treatment facilities (27 mi [IQR 11–52], 21 mi [IQR 10–39], p = 0.15). On multivariable logistic regression controlling for insurance, T‐stage, PORT location, distance to PORT facility; radiation treatment at an outside facility was independently associated with a higher likelihood of delay (OR 1.94, 95% CI 1.03–3.74, p = 0.043). Patients with more advanced T stages had higher likelihood of PORT delay when compared to T1 (T2–T4 OR = 5.06, 3.85, 3.49; all p < 0.02). Table 3 illustrates the result of the multivariable logistic regression.
TABLE 3.
Multivariable Logistic Regression Predicting a delay in receiving PORT.
| Characteristics | OR | 95% CI | p |
|---|---|---|---|
| Insurance | |||
| Private | — | — | |
| Medicaid/Medicare | 0.96 | 0.50, 1.84 | 0.893 |
| Other/unknown | 1.15 | 0.37, 4.32 | 0.822 |
| T‐stage | |||
| 1 | — | — | |
| 2 | 5.06 | 1.63, 16.8 | 0.006 |
| 3 | 3.85 | 1.32, 11.7 | 0.015 |
| 4 | 3.49 | 1.27, 9.95 | 0.016 |
| PORT at home institution | |||
| No | — | — | |
| Yes | 1.94 | 1.03, 3.74 | 0.043 |
| Distance to PORT facility | 1 | 1.00, 1.01 | 0.235 |
| Complications | |||
| No | — | — | |
| Yes | 1.76 | 0.85, 3.82 | 0.138 |
3.4. Survival Outcomes Based on PORT Delay and TPT
With a median follow‐up of 30.9 months (IQR 11.5–44.6), 28% (n = 64) of patients developed recurrent disease. This includes 22% local (n = 14), 16% regional (n = 10), and 63% distant (n = 40).
PORT delay did not significantly impact 2‐year OS or PFS. Kaplan–Meier analysis showed no significant association between PORT delay and OS or PFS (Figure 2). Patients with PORT delay displayed a 2‐year OS of 81.9% (95% CI [76%–89%]) compared to 72.3% [77%–89%] for those without delay (log‐rank; p = 0.68), and a 2‐year PFS of 75.7% [65%–87%] and 73.2% [61%–86%] (log‐rank p = 0.63) (Figure 2). Kaplan–Meyer analysis for TPT stratified by greater or less that 50th percentile of TPT is shown in (Figure 3).
FIGURE 2.
Kaplan–Meier curve illustrating the difference in overall survival by delay status. A log‐rank statistic is depicted. Median survival was not reached within 2 years.
FIGURE 3.
Kaplan–Meier curve illustrating the difference in Overall Survival by treatment package time (TPT). A log‐rank statistic is depicted.
On multivariable Cox regression model (Table 4) PORT delay was not associated with OS (HR X, 95% CI Y, p = z) and PFS (HR X, 95% CI Y, p = z). Black race was independently associated with worse PFS (HR 2.82, 95% CI [1.10–7.21], p = 0.031) but not OS. Across N stages 2 and 3, there was a stepwise increased risk of mortality for both OS (N3 and N2 relative to N0; HR = 8.69, 6.18; p < 0.001) and PFS (N3 and N2 relative to N0; HR = 7.96, 4.06; p < 0.001). T‐stage did not significantly impact PFS or OS. For PFS, a primary site of the skin/scalp was associated with worse PFS compared to oral cavity tumors (HR 4.7, 95% CI 2.05–10.8, p < 0.001).
TABLE 4.
Cox Regression predicting overall and progression‐free survival controlling for tumor and sociodemographic characteristics.
| Overall survival | Progression‐free survival | |||||
|---|---|---|---|---|---|---|
| Characteristic | HR | 95% CI | p | HR | 95% CI | p |
| PORT delay | ||||||
| No | — | — | — | — | ||
| Yes | 0.76 | 0.38, 1.51 | 0.4 | 0.62 | 0.33, 1.14 | 0.12 |
| Age | 1.04 | 1.01, 1.07 | 0.019 | 1.01 | 0.98, 1.03 | 0.5 |
| Race | ||||||
| White | — | — | — | — | ||
| Black | 2.33 | 0.74, 7.39 | 0.2 | 2.82 | 1.10, 7.21 | 0.031 |
| Other | 0.99 | 0.12, 8.25 | > 0.9 | 2.13 | 0.57, 7.96 | 0.3 |
| N‐stage | ||||||
| 0 | — | — | — | — | ||
| 1 | 2.84 | 0.77, 10.4 | 0.12 | 0.92 | 0.28, 3.00 | 0.9 |
| 2 | 6.18 | 2.46, 15.5 | < 0.001 | 4.06 | 1.82, 9.03 | < 0.001 |
| 3 | 8.69 | 3.62, 20.8 | < 0.001 | 7.96 | 3.62, 17.5 | < 0.001 |
| T‐stage | ||||||
| 1 | — | — | — | — | ||
| 2 | 0.74 | 0.18, 3.00 | 0.7 | 1.27 | 0.30, 5.42 | 0.7 |
| 3 | 1.26 | 0.37, 4.30 | 0.7 | 2.75 | 0.77, 9.77 | 0.12 |
| 4 | 1.58 | 0.51, 4.84 | 0.4 | 1.9 | 0.56, 6.45 | 0.3 |
| Cancer subsite | ||||||
| Oral cavity | — | — | — | — | ||
| Oropharynx | 0 | 0.00, Inf | > 0.9 | — | — | — |
| Larynx/hypopharynx | 1.27 | 0.56, 2.84 | 0.6 | 1.42 | 0.67, 2.98 | 0.4 |
| Nasal cavity/paranasal sinuses | 2.27 | 0.57, 9.02 | 0.2 | 2.09 | 0.69, 6.31 | 0.2 |
| Salivary | 2.28 | 0.61, 8.56 | 0.2 | 1.19 | 0.26, 5.39 | 0.8 |
| Skin/scalp | 1.9 | 0.62, 5.83 | 0.3 | 4.7 | 2.05, 10.8 | < 0.001 |
| PORT at home institution | ||||||
| Yes | — | — | — | — | ||
| No | 1.22 | 0.64, 2.31 | 0.6 | 0.94 | 0.55, 1.61 | 0.8 |
Abbreviations: CI = confidence interval; OR = odds ratio.
4. Discussion
In this study encompassing 236 HNC patients who underwent definitive surgical resection and adjuvant radiation therapy, a substantial proportion (73.2%) experienced delays in PORT. Radiation treatment at facilities different than the location of primary resection was independently associated with a higher likelihood of PORT delay. Within our cohort, delay in treatment greater than the 6 weeks did not significantly impact 2‐year OS or PFS.
Although the number of patients experiencing PORT delay in our cohort is substantial, it aligns with the broader literature consistently indicating a prevalence of PORT delays. Our institutional PORT delay rate (73.2%) surpasses that of several national and single‐institution studies, which have reported rates of greater than 50% [16, 17]. This may be secondary to our expansive catchment area and subsequently logistical delays due to long travel distances. Increased distance to treatment facility has been found to be a factor for noncompliance [18]. On average, as indicated in our analysis, patients who experienced delays lived further from their institution of primary resection; however, this was not an independent predictor of delay on multivariable models. Fundamentally, our study, and the various others published in the literature, indicate that there is much work needed to be done to abide by the relatively new standards put forth by AHNS and CoC.
To identify novel predictors of delay in PORT, our study found that radiation treatment at an outside facility was associated with an increased risk of PORT delay, consistent with Chen et al. [19], but in contrast to Schoonbeek et al. [20] Forty‐seven percent of VUMC patients received PORT at an outside facility. On the multivariable model, after controlling for complications, more advanced T stage was associated with PORT delay. Additionally, radiation therapy at an outside facility was independently associated with increased odds of PORT delay even after controlling for distance from a patient's surgical facility. This suggests that delays are not simply due to distance traveled but other factors associated with new treatment facilities, such as logistical barriers when transferring care and provider communication. For patients with outside radiation therapy facility treatment, the diagnosis‐to‐surgery and radiation referral‐to‐PORT intervals are longer than for patients who receive institutional radiation treatment. This suggests that transfers of care may be a contributing factor in PORT delay. In many scenarios, the distance to radiation facilities is reduced when receiving treatment at outside facilities, especially for an institution such as VUMC which captures patients from multiple states. Although additional studies are needed to elucidate the exact mechanism of our observation, this suggests the need for strengthened patient care navigation networks and enhanced communication with external treatment centers. We did not identify any other major sociodemographic predictors of treatment delay, although there is considerable literature establishing the impact of social determinants of health on HNC outcomes and treatment [21, 22].
A study [13] found that there was no longer a survival benefit to academic centers when patients experienced care fragmentation, and that fragmentation of care was associated with worse OS. Our lack of significant impact of PORT delay on 2‐year OS or PFS contrasts with established literature emphasizing the crucial role of timely PORT in improving survival outcomes [23, 24]. In a systematic review of literature from 1995 to 2022, delay beyond 6 weeks was shown to worsen OS and PFS [23]. In a multicenter cohort study from Canadian academic centers from 2005 to 2019, initiation of PORT within 42 days was associated with improved survival [24]. This challenges the conventional wisdom and suggests a multifactorial interplay influencing HNC patient survival, and the need for multi‐institution studies of PORT delay and outcomes. It should be noted that the CoC and AHNS quality metric only mentions head and neck squamous cell carcinoma, but our study includes many other HNC subtypes, as shown in Table 2. Our findings may be impacted by the inclusion of less aggressive HNC subtypes such as advanced cutaneous and salivary malignancies as the need for timely PORT in this patient population is perhaps less crucial.
Our study is not without limitations. The small sample size and retrospective nature constrain the generalizability of our findings. At our institution, we have a, particularly, homogenous HNC patient population, higher proportion of Caucasian males, when compared to other tertiary cancer centers across the country and recognize that this limits the diversity of patient characteristics and generalizability of our findings. Exclusion of patients with missing timeline data introduces potential bias. A more extended follow‐up may unveil survival differences; however, a majority of HNC recurrences occur within two years [14, 25] and, therefore, we are likely capturing a majority of recurrences and cancer‐related death with our 2‐year follow‐up data [25, 26]. As a single institution, we acknowledge the need for larger, multi‐institutional studies to provide a more comprehensive understanding of PORT delay on a national scale.
The disconnect between PORT delay and survival outcomes prompts a reevaluation of the current emphasis on minimizing PORT delay as the sole metric for quality improvement in HNC care. As institutions nationwide strive to meet the CoC and AHNS quality metrics, our study suggests that additional factors, like radiation facility location, may contribute more significantly. A nuanced understanding of these factors, along with improved patient care navigation networks and enhanced communication with outside facilities, may be essential for addressing the complexities surrounding PORT delays and improving survival outcomes for HNC patients.
5. Conclusions
Within this single institution study, nearly three‐fourths of patients had delays in PORT. Radiation therapy at an outside facility was an independent predictor of PORT delay. Contrary to the current prevailing sentiment, delay in treatment and location of PORT did not significantly impact 2‐year OS or PFS.
Conflicts of Interest
The authors declare no conflicts of interest.
Supporting information
Data S1.Supporting Information.
Funding: This work was supported by the Vanderbilt Clinical Oncology Research Career Development Award (NCI2K12CA090625‐22A1).
Data Availability Statement
The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.
References
- 1. Caudell J. J., Gillison M. L., Maghami E., et al., “NCCN Guidelines® Insights: Head and Neck Cancers, Version 1.2022,” Journal of the National Comprehensive Cancer Network 20, no. 3 (2022): 224–234, 10.6004/jnccn.2022.0016. [DOI] [PubMed] [Google Scholar]
- 2. Lavaf A., Genden E. M., Cesaretti J. A., Packer S., and Kao J., “Adjuvant Radiotherapy Improves Overall Survival for Patients With Lymph Node‐Positive Head and Neck Squamous Cell Carcinoma,” Cancer 112, no. 3 (2008): 535–543, 10.1002/cncr.23206. [DOI] [PubMed] [Google Scholar]
- 3. Ang K. K., Trotti A., Brown B. W., et al., “Randomized Trial Addressing Risk Features and Time Factors of Surgery Plus Radiotherapy in Advanced Head‐And‐Neck Cancer,” International Journal of Radiation Oncology, Biology, Physics 51, no. 3 (2001): 571–578, 10.1016/s0360-3016(01)01690-x. [DOI] [PubMed] [Google Scholar]
- 4. Murphy C. T., Galloway T. J., Handorf E. A., et al., “Survival Impact of Increasing Time to Treatment Initiation for Patients With Head and Neck Cancer in the United States,” Journal of Clinical Oncology: Official Journal of the American Society of Clinical Oncology 34, no. 2 (2016): 169–178, 10.1200/JCO.2015.61.5906. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5. Graboyes E. M., Garrett‐Mayer E., Ellis M. A., et al., “Effect of Time to Initiation of Postoperative Radiation Therapy on Survival in Surgically Managed Head and Neck Cancer,” Cancer 123, no. 24 (2017): 4841–4850, 10.1002/cncr.30939. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6. George J. R., Yom S. S., and Wang S. J., “Combined Modality Treatment Outcomes for Head and Neck Cancer: Comparison of Postoperative Radiation Therapy at Academic vs Nonacademic Medical Centers,” JAMA Otolaryngology—Head & Neck Surgery 139, no. 11 (2013): 1118–1126, 10.1001/jamaoto.2013.4539. [DOI] [PubMed] [Google Scholar]
- 7. Levy D. A., Li H., Sterba K. R., et al., “Development and Validation of Nomograms for Predicting Delayed Postoperative Radiotherapy Initiation in Head and Neck Squamous Cell Carcinoma,” JAMA Otolaryngology—Head & Neck Surgery 146, no. 5 (2020): 455, 10.1001/jamaoto.2020.0222. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8. Graboyes E. M., Kompelli A. R., Neskey D. M., et al., “Association of Treatment Delays With Survival for Patients With Head and Neck Cancer: A Systematic Review,” JAMA Otolaryngology—Head & Neck Surgery 145, no. 2 (2019): 166–177, 10.1001/jamaoto.2018.2716. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9. Dogan N., King S., Emami B., et al., “Assessment of Different IMRT Boost Delivery Methods on Target Coverage and Normal‐Tissue Sparing,” International Journal of Radiation Oncology, Biology, Physics 57, no. 5 (2003): 1480–1491, 10.1016/s0360-3016(03)01569-4. [DOI] [PubMed] [Google Scholar]
- 10. Lee N. Y., O'Meara W., Chan K., et al., “Concurrent Chemotherapy and Intensity‐Modulated Radiotherapy for Locoregionally Advanced Laryngeal and Hypopharyngeal Cancers,” International Journal of Radiation Oncology, Biology, Physics 69, no. 2 (2007): 459–468, 10.1016/j.ijrobp.2007.03.013. [DOI] [PubMed] [Google Scholar]
- 11. Chen A. Y., Pavluck A., Halpern M., and Ward E., “Impact of Treating facilities' Volume on Survival for Early‐Stage Laryngeal Cancer,” Head & Neck 31, no. 9 (2009): 1137–1143, 10.1002/hed.21072. [DOI] [PubMed] [Google Scholar]
- 12. Kubicek G. J., Wang F., Reddy E., Shnayder Y., Cabrera C. E., and Girod D. A., “Importance of Treatment Institution in Head and Neck Cancer Radiotherapy,” Otolaryngology and Head and Neck Surgery 141, no. 2 (2009): 172–176, 10.1016/j.otohns.2009.03.019. [DOI] [PubMed] [Google Scholar]
- 13. Chen M. M., Megwalu U. C., Liew J., Sirjani D., Rosenthal E. L., and Divi V., “Regionalization of Head and Neck Cancer Surgery May Fragment Care and Impact Overall Survival,” Laryngoscope 129, no. 6 (2019): 1413–1419, 10.1002/lary.27440. [DOI] [PubMed] [Google Scholar]
- 14. Žumer B., Pohar Perme M., Jereb S., and Strojan P., “Impact of Delays in Radiotherapy of Head and Neck Cancer on Outcome,” Radiation Oncology 15, no. 1 (2020): 202, 10.1186/s13014-020-01645-w. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15. Zanoni D. K., Patel S. G., and Shah J. P., “Changes in the 8th Edition of the American Joint Committee on Cancer (AJCC) Staging of Head and Neck Cancer: Rationale and Implications,” Current Oncology Reports 21, no. 6 (2019): 52, 10.1007/s11912-019-0799-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16. Lorenz F. J., Mahase S. S., Miccio J., King T. S., Pradhan S., and Goyal N., “Update on Adherence to Guidelines for Time to Initiation of Postoperative Radiation for Head and Neck Squamous Cell Carcinoma,” Head & Neck 45, no. 7 (2023): 1676–1691, 10.1002/hed.27380. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17. Sawaf T., Virgen C. G., Renslo B., et al., “Association of Social‐Ecological Factors With Delay in Time to Initiation of Postoperative Radiation Therapy: A Prospective Cohort Study,” JAMA Otolaryngology—Head & Neck Surgery 149, no. 6 (2023): 477–484, 10.1001/jamaoto.2023.0308. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18. Zheleva V., Nelson R. A., Dumitra S., Vora N. L., and Lai L. L., “Time to Adjuvant Radiotherapy in Breast Cancer Affects Survival: Implications for the American College of Surgeons Commission on Cancer Quality Metrics,” Annals of Surgical Oncology 27, no. 8 (2020): 2614–2625, 10.1245/s10434-020-08326-8. [DOI] [PubMed] [Google Scholar]
- 19. Chen M. M., Harris J. P., Orosco R. K., Sirjani D., Hara W., and Divi V., “Association of Time Between Surgery and Adjuvant Therapy With Survival in Oral Cavity Cancer,” Otolaryngology and Head and Neck Surgery 158, no. 6 (2018): 1051–1056, 10.1177/0194599817751679. [DOI] [PubMed] [Google Scholar]
- 20. Schoonbeek R. C., Zwertbroek J., Plaat B. E. C., et al., “Determinants of Delay and Association With Outcome in Head and Neck Cancer: A Systematic Review,” European Journal of Surgical Oncology: The Journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology 47, no. 8 (2021): 1816–1827, 10.1016/j.ejso.2021.02.029. [DOI] [PubMed] [Google Scholar]
- 21. Sharma R. K., Patel S., Ye W., and Rohde S. L., “Association of Social Vulnerability on Survival, Treatment, and Presentation in Oral Cavity Cancer,” Head & Neck 45, no. 9 (2023): 2185–2197, 10.1002/hed.27447. [DOI] [PubMed] [Google Scholar]
- 22. Patel U. A. and Brennan T. E., “Disparities in Head and Neck Cancer: Assessing Delay in Treatment Initiation,” Laryngoscope 122, no. 8 (2012): 1756–1760, 10.1002/lary.23357. [DOI] [PubMed] [Google Scholar]
- 23. Sun K., Tan J. Y., Thomson P. J., and Choi S. W., “Influence of Time Between Surgery and Adjuvant Radiotherapy on Prognosis for Patients With Head and Neck Squamous Cell Carcinoma: A Systematic Review,” Head & Neck 45, no. 8 (2023): 2108–2119, 10.1002/hed.27401. [DOI] [PubMed] [Google Scholar]
- 24. Liao C. T., Kang C. J., Lee L. Y., et al., “Association Between Multidisciplinary Team Care Approach and Survival Rates in Patients With Oral Cavity Squamous Cell Carcinoma,” Head & Neck 38, no. Suppl 1 (2016): E1544–E1553, 10.1002/hed.24276. [DOI] [PubMed] [Google Scholar]
- 25. Beswick D. M., Gooding W. E., Johnson J. T., and Branstetter B. F., “Temporal Patterns of Head and Neck Squamous Cell Carcinoma Recurrence With Positron‐Emission Tomography/Computed Tomography Monitoring,” Laryngoscope 122, no. 7 (2012): 1512–1517, 10.1002/lary.23341. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26. Leemans C. R., Tiwari R., Nauta J. J., van der Waal I., and Snow G. B., “Recurrence at the Primary Site in Head and Neck Cancer and the Significance of Neck Lymph Node Metastases as a Prognostic Factor,” Cancer 73, no. 1 (1994): 187–190, . [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data S1.Supporting Information.
Data Availability Statement
The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.