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Keywords:

  • Gamma Knife;
  • radiosurgery;
  • chronobiology;
  • non–small cell lung cancer;
  • circadian rhythm;
  • time of day;
  • survival;
  • local control;
  • brain metastases

Abstract

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. FUNDING SOURCES
  8. CONFLICT OF INTEREST DISCLOSURE
  9. REFERENCES

BACKGROUND

This study tested the hypothesis that time of day of treatment with stereotactic radiosurgery (SRS) has an effect on local control (LC) and overall survival (OS) in a large cohort of patients with non–small cell lung cancer (NSCLC) brain metastases.

METHODS

At Washington University in St. Louis, 437 patients with NSCLC were treated with SRS for NSCLC brain metastases. Receiver operating characteristics analysis was used to identify an optimal cut-point for OS relative to time of day. Kaplan-Meier log-rank statistics, and Cox regression univariate and multivariate analysis were employed to isolate any independent effect of treatment time on OS and LC. Matched-pair analysis was performed to isolate any independent effect of time on OS and LC of day while controlling for confounding variables.

RESULTS

Receiver operating characteristics analysis identified a cut-point of 11:41 AM as providing the highest predictive value for OS. On univariate analysis, late SRS was associated with decreased OS, as was age, Karnofsky performance status, risk-stratification schemes, extracranial disease status, and overall burden of brain metastases. On univariate analysis for LC, late SRS was associated with decreased LC, as was burden of brain metastases. On multivariate analysis, only Graded Prognostic Assessment remained predictive of OS, and total number of targets and total tumor volume remained predictive of LC. Matched-pair analysis demonstrated no significant effect of time of day on LC or OS.

CONCLUSIONS

Although earlier treatment appears to be associated with improved LC and OS, treatment time fails to remain significant when accounting for confounding variables. Cancer 2013;119:3563–3569.. © 2013 American Cancer Society.


INTRODUCTION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. FUNDING SOURCES
  8. CONFLICT OF INTEREST DISCLOSURE
  9. REFERENCES

The brain is one of the most common sites of metastases, occurring in 20% to 50% of patients with lung cancer. Multiple treatment options exist for the management of brain metastases, including surgery, whole-brain radiation therapy (WBRT), stereotactic radiosurgery, or combinations thereof. One-year local control (LC) after radiosurgery ranges from 67% to 90%.[1-4] Established factors predicting for improved LC after radiosurgery include smaller tumor size, nonradioresistant histology, and the addition of WBRT.[5-7] Predictors of overall survival (OS) include Recursive Partitioning Analysis (RPA), Score Index for Radiosurgery (SIR), and the newer Graded Prognostic Assessment (GPA) indices, which account for the effects of age, performance status, extracranial disease status, and now number of brain metastases and histology.[8-10] Failure to control brain metastases is the primary cause of neurologic decline, and neurologic death is a significant contributor to the poor OS in this population.[11] Although a number of radiosensitizers have been tested to improve LC, results have been unimpressive to date, and none have been approved for this indication.[11-13] Furthermore, in this typically frail population, side effects of systemic radiosensitizers may be significant. Thus, methods to improve LC of brain metastases with minimal toxicity are sorely needed in this population.

The interplay between circadian rhythm proteins, the cell cycle, and DNA damage repair has been an area of active basic science research over the last decade. For example, recently published data has shown that a critical circadian rhythm protein, CLOCK, accumulates at double-stranded DNA break sites following ionizing radiation, and cells with down-regulation of CLOCK protein are more sensitive to ionizing radiation.[14] Furthermore, multiple studies have demonstrated that mammalian cells vary in their sensitivity to radiation depending on their cell cycle phase, with cells in the G2/M phase demonstrating the greatest sensitivity to radiation-induced damage.[15, 16] Murine tissues such as bone marrow and intestinal crypt cells have been shown to display variations in radiosensitivity throughout the day, with peak radiotherapy-induced apoptosis occurring between 6:00 AM and 9:00 AM.[17-19] In addition to rapidly proliferating cells such as bone marrow and intestinal crypt cells, the circadian rhythm–dependent radiosensitivity of tissues has also been shown to exist in slowly proliferating tissues such as the parotid gland.[20] If something as simple as time of day could improve control rates after radiotherapy, there would be great appeal from a simplicity, cost, and toxicity standpoint relative to technical or drug-related means. However, limited data exist on the impact of circadian rhythms on clinical outcomes.

In the only publication to date that examined the effect of circadian rhythm on treatment outcomes for patients with brain metastases, investigators from the University of Virginia identified 97 patients who received Gamma Knife stereotactic radiosurgery (SRS) for brain metastases from non–small cell lung cancer (NSCLC), and found that patients treated prior to 12:30 PM had significant improvements in LC (97% versus 67%, P = .014) and median OS (9.5 months versus 5 months, P = .025) compared with patients receiving treatment after 12:30 PM. On multivariate analysis, early treatment time (P = .004) and RPA class (P < .001) remained predictive of improved OS.[21]

Results of the aforementioned study have not yet been replicated. The purpose of our study was to identify factors predictive of LC and OS after treatment of NSCLC brain metastases with SRS, and determine whether time of day was associated with improvements in these outcomes in an independent set of patients treated at our institution.

MATERIALS AND METHODS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. FUNDING SOURCES
  8. CONFLICT OF INTEREST DISCLOSURE
  9. REFERENCES

As part of an institutional review board–approved registry of patients treated with Gamma Knife SRS at Washington University in St. Louis, St. Louis, Missouri, 437 consecutive patients with brain metastases from pathologically confirmed NSCLC who were treated from 1998 to 2011 were identified. Exclusion criteria included patients with second malignancies in the 2 years prior to treatment (except basal cell carcinoma/squamous cell carcinoma of the skin), or patients whose tumors had small cell/neuroendocrine features. For patients who had more than 1 session of SRS, only the first session was analyzed. Baseline patient, tumor, and treatment factors were retrospectively extracted from the medical record, as seen in Tables 1 and 2. Local control was defined as absence of radiographic progression in the lesions treated with SRS through review of brain magnetic resonance imaging (MRI) reports and independent review of the MRI itself when available. OS was defined as the absence of death secondary to any cause.

Table 1. Patient Characteristics: Categorical Variables
CharacteristicsSRS Before 11:41 AM % of PatientsSRS After 11:41 AM % of PatientsP (Chi-Square Test)
  1. Values in bold indicate statistical significance.

  2. Abbreviations: AC, adenocarcinoma; AS, adenosquamous carcinoma; SRS, stereotactic radiosurgery; KPS, Karnofsky performance status; LCC, large-cell carcinoma; NSCLC NOS, non-small cell lung cancer not otherwise specified; RPA, recursive partition analysis; SCC, squamos cell carcinoma; SIR, Score Index for Radiosurgery; WBRT, whole-brain radiotherapy.

Female4750.43
Nonwhite race1513.39
Gamma Knife model (B, C, Perfexion)24, 45, 3126, 41, 33.72
Prior steroid use8989.93
Extracranial metastases3541.26
Prior WBRT4058.0005
Prior brain metastatectomy1715.67
Prior chemotherapy6362.79
Prior lung radiotherapy4539.29
KPS (60, 70, 80, 90)1, 11, 56, 321, 11, 67, 21.07
RPA class (1, 2)30, 7030, 70.95
SIR class (0, 1, 2)42, 40, 1848, 41, 12.16
Histology (SCC, AC, NSCLC NOS, AS, LCC)10, 54, 33, 1, 213, 52, 32, 1, 1.84
Table 2. Patient Characteristics: Continuous Variables
CharacteristicsSRS Before 11:41 AM (25th-75th percentile)SRS After 11:41AM (25th-75th percentile)P (Wilcoxon Rank-Sum Test)
  1. All data are presented as median unless otherwise noted.

  2. a

    Mean data presented.

  3. Abbreviations: SRS, stereotactic radiosurgery; GPA score, graded prognostic assessment.

Age, years6159.09
GPA score2.52.25.008
Total no. of shots57.5.0001
Total no. of targets1 (1–2)2 (1–3)<.0001
Conformality index1.61.6.51
Dose to periphery of tumor, cGy20001800.007
Prescription isodose linea, %51.9(50–50)52.4 (50–55).04
Largest tumor volume, mm319002200.21
Total tumor volume, mm320582400.06
Time from diagnosis to brain metastasis, days0 (0–12)0 (0–10).54
Time from diagnosis of brain metastasis to GKRS, days4068.01
Treatment length, minutes3341<.0001

After undergoing stereotactic frame placement and MRI and computed tomography brain imaging, patients underwent SRS treatment between 9:12 AM and 6:02 PM. The scheduling of treatment was generally performed with consideration of each patient's preference and appointment availability but without overt consideration of any patient clinical or pathologic features.

Using a combination of graphical diagnostic plots, minimum P value approach with adjusted P values, and receiver operating characteristic (ROC) curves[22] baseline characteristics by time of day were evaluated with the Wilcoxon rank-sum test for continuous variables and Fisher's exact test for categorical variables. Survival analyses by time of day were performed using the Kaplan-Meier (KM) method, and comparisons of OS and LC were performed using the log-rank test. Cox regression univariate analysis was performed to determine the significance of relevant patient, tumor, and treatment variables with regard to OS and LC, with a subsequent multivariate Cox regression analysis performed using stepwise selection methodology. Matched pair analysis was performed to generate an analytic data set of matched cases and controls, using simple random sampling without replacement to identify independent samples stratified on one or more matched criteria. The alpha level was set at 0.05 for each statistical test.

RESULTS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. FUNDING SOURCES
  8. CONFLICT OF INTEREST DISCLOSURE
  9. REFERENCES

The median age of the entire cohort was 60 years. A total of 189 patients had previously received WBRT, and 60 patients had prior brain metastectomies. Based on the derived cut-point, we identified a cut-point of 11:41 AM as providing the greatest degree of discrimination between morning and afternoon treatments for OS. A total of 189 patients were identified who were treated between 9:12 AM and 11:40 AM, and 248 patients were treated between 11:41 AM and 6:02 PM. Tables 1 and 2 present a comparison of patient, tumor, and treatment characteristics for patients treated before and after 11:41 AM. Patients treated before 11:41 AM had significantly lower rates of prior WBRT, a higher median GPA score, and shorter time from diagnosis of metastases to SRS treatment. Likewise, patients treated in the morning had fewer brain metastases (targets), and as a consequence fewer shots and a shorter treatment time. There was a trend for patients treated prior to 11:41 AM to have smaller total tumor volumes, with associated treatment to significantly higher doses, in keeping with standard SRS practice. Plan quality between groups was similar, as shown by comparison of median conformality indices.

Median follow-up for the entire group was 18 months. KM-estimated 1- and 2-year LC and OS for all patients was 63% and 43%, and 30% and 12%, respectively. In an unadjusted KM comparison looking only at the impact of time of day, 1-year LC was significantly higher for patients treated prior to 11:41 AM (74% versus 54%, P = .016). Similarly, median OS was significantly higher (10 versus 8 months, P = .012) for patients treated prior to 11:41 AM.

Factors predictive of decreased OS on univariate analysis are presented in Table 3. Treatment after 11:41 AM was predictive of worse OS. In keeping with the prior literature, patient variables such as age, Karnofsky performance status, and the commonly employed classification schemes (SIR, RPA, and GPA) were all predictive of OS. Likewise, presence of extracranial metastases, lack of control of the lung primary, and progressive systemic disease were all predictors of poor OS. In addition, we identified multiple surrogates for brain metastases burden as predictive of OS (number of shots, largest tumor volume, and total tumor volume). However, on multivariate analysis (Table 4), only GPA score remained an independent predictor of OS.

Table 3. Cox Regression Univariate Analysis of Post-SRS Overall Survivala
CharacteristicsHR95% CIP
  1. a

    Only statistically significant variables are reported.

  2. b

    When compared to KPS 90.

  3. c

    When compared to RPA class 1.

  4. d

    As score increases, HR for death decreases, thus HR <1.

  5. e

    RPA: Staging system in which a stage of 1 to 3 is assigned based on the patient's KPS, age, control of primary cancer, and presence of extracranial metastases.

  6. f

    GPA: Scoring system in which a point value of 0, 0.5, or 1 is assigned to 4 prognostic factors: age, KPS, no. of cranial metastases, and presence of extracranial metastases.

  7. g

    SIR: Scoring system in which a score of 0 to 2 was tallied for 5 prognostic factors: age, KPS, systemic disease status, size of largest lesion, and number of lesions. Patients with scores of 1–3 points are assigned to class 1, class 2 is 4–7 points, and class 3 is 8–10 points.

  8. Abbreviations: CI, confidence interval; GPA, graded prognostic assessment; HR, hazard ratio; KPS, Karnofsky performance status; RPA, recursive partition analysis; SIR, score index for radiosurgery; WBRT, whole-brain radiotherapy.

Treatment after 11:41 AM1.301.06–1.59.011
KPS 60b6.302.30–17.24.0003
KPS 70b2.311.61–3.32<.0001
KPS 80b1.731.35–2.20<.0001
Extracranial metastases2.091.65–2.66<.00001
No control of primary lung tumor1.431.12–1.82.003
Prior WBRT1.331.07–1.65.01
Age1.021.01–1.03.00003
RPA class 2ce1.861.44–2.40<.00001
GPA scoredf0.560.48–0.65<.00001
SIR classdg0.750.68–0.83<.00001
Progressive systemic disease2.081.47–2.94.00003
Total no. of shots1.031.01–1.05.001
Total no. of targets1.101.03–1.18.006
Log (largest tumor volume)1.151.06–1.24.0008
Log (total tumor volume)1.171.07–1.27.0003
Table 4. Multivariate Cox Regression Analysis of Post–Stereotactic Radiosurgery Overall Survival
CharacteristicsHazard Ratio95% CIP
Treatment After 11:41 AMN/AN/A.11
Graded Prognostic Assessment score0.560.48–0.65<.0001

Factors predictive of decreased LC on univariate analysis are presented in Table 5. Treatment after 11:41 AM was predictive of worse LC. In addition, surrogates for brain metastases burden also remained predictive of LC (number of shots, number of targets, largest tumor volume, and total tumor volume). However, on multivariate analysis (Table 6), only total number of targets and total tumor volume remained independent predictors of LC.

Table 5. Univariate Cox Regression Analysis of Post–Stereotactic Radiosurgery Local Control
CharacteristicsHazard Ratio95% CIP
Treatment after 11:41 AM1.591.03–2.46.035
Total no. of targets1.181.03–1.35.018
Total no. of shots1.051.02–1.09.005
Log (total tumor volume)1.481.22–1.80.00008
Log (largest tumor volume)1.411.17–1.70.0003
Table 6. Multivariate Cox Regression Analysis of Post–Stereotactic Radiosurgery Local Control
CharacteristicsHazard Ratio95% CIP
Treatment after 11:41 AMN/AN/A.12
Total no. of targets1.181.03–1.35.017
Log (total tumor volume)1.491.22–1.82<.0001

Using the variables predictive of OS on multivariate analysis, a matched pair analysis was performed to determine if OS was significantly different based on time of day when known confounding variables were accounted for. A total of 126 pairs of patients (252 total) were matched on Karnofsky performance status and GPA score, and no difference in OS was identified between patients treated before or after 11:41 AM (P = .29) (Fig. 1). Similarly, matched pair analysis was performed for LC. Ninety-one pairs of patients (182 total) were matched on total number of shots and total tumor volume, and no difference in LC was identified between matched pairs (P = .19) (Fig. 2).

image

Figure 1. Kaplan-Meier curves of overall survival following matched pair analysis of 126 pairs of patients.

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image

Figure 2. Kaplan-Meier curves of local control following matched pair analysis of 91 pairs of patients.

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DISCUSSION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. FUNDING SOURCES
  8. CONFLICT OF INTEREST DISCLOSURE
  9. REFERENCES

We sought to identify factors predictive of OS and LC after SRS for brain metastases, with a specific goal of confirming improved outcomes for patients treated earlier in the day, as demonstrated by Rahn et al.[21] After identifying an optimal cut-point of 11:41 AM to discriminate the effect of time of day on OS, we also demonstrated what appeared to be improved outcomes for patients treated earlier in the day. However, when accounting for additional factors predictive of OS and LC on multivariate analysis, time of day failed to remain significantly associated with either outcome. Furthermore, when performing a matched pair analysis to control for the identified confounding variables, time of day was again not a significant predictor of OS or LC. Thus, we conclude that the effect of improved outcomes for patients with NSCLC who receive SRS and are treated early appeared to be driven by more favorable selection of patient and tumor characteristics rather than an independent effect of time alone. Although there are no physician-directed policies in place at our institution for the arrangement of treatment times, in discussions with the nursing team that is primarily responsible for scheduling, there has been an unofficial practice that patients with multiple metastases and poorer performance are brought in for treatment later in the day, given their difficulty in arriving at the treatment facility early in the morning and the challenges in estimating overall treatment time in particular for multiple metastases.

In the study from the University of Virginia, Rahn et al compared outcomes of 97 patients who received SRS treatment for NSCLC based on a time of day cutoff of 12:30 PM.[21] This cutoff was chosen based on an exploratory analysis leading to 2 time brackets equally dividing the range of treatment options. This was felt to provide a convenient notation of risk for clinical and statistical applications, but the description of the methodology would indicate that specific statistical methods well known to identify optimal cutoffs (such as ROC analysis) were not employed. In the present analysis, we employed multiple standard methods for identifying an optimal cutoff, and thus it is unlikely that our negative results for time of day are a consequence of suboptimal time selection.[22]

The difference in statistical power between the studies may also explain our different conclusions. The study from the University of Virginia included only 97 patients, and these numbers were further reduced when looking at outcomes such as 3-month LC, which included only 36 patients in the early group and 12 in the late group. Using a chi-square analysis as was performed with those patient numbers could lead to dramatic changes in levels of significance with 1 or 2 patients having different outcomes. Furthermore, whereas the early and late patient groups were not significantly different with respect to baseline patient, tumor, and treatment variables, it is intriguing that patient age, time from diagnosis to SRS treatment, median number of tumors, and number of tumors treated were numerically greater in the late group. In our analysis of 437 patients, we saw similar (though significant) differences between groups, and these were clear predictors of OS and LC. Thus, the absence of significant differences in baseline characteristics in the University of Virginia study could be as a result of insufficient patient numbers. Finally, in order to verify that our results were not biased by the imbalance between the groups, we employed the additional method of matched pair analysis. As seen in Figs. 1 and 2, despite matching on variables predictive of OS and LC on multivariate analysis, we found no significant effect of time of day on outcomes.

Other clinical studies to date have also shown conflicting results. A prospective randomized trial of head and neck cancer treated with radiotherapy examined the role of time of day on rates of oral mucositis and found that patients receiving radiotherapy between 8:00 and 10:00 AM were significantly less likely to lose weight or develop grade 3 or greater mucositis if they received ≥ 66 Gy, or smoked during therapy.[23] Shukla et al published a prospective trial of 229 patients with stage IIB to IIIB cervical cancer who were randomized to morning (8:00-10:00 AM) and evening (6:00-8:00 PM) radiotherapy arms. The investigators found significantly greater grades III and IV diarrhea in patients in the morning arm as compared with those in the evening arm (14% versus 5%, P < .05), but did not find a difference in other toxicity rates (ie, skin, nausea, bladder, hematologic), or tumor response (ie, complete response, partial response, or progressive disease) between the 2 arms.[24]

There are limitations to our analysis as well. The study was performed as a retrospective analysis and, therefore, is limited by its nature; however, in our univariate and multivariate analyses, we incorporated multiple validated prognostic indices, quality indices, and treatment indices which may control for some of the limitations of a retrospective analysis. Also, because our study was limited to 437 patients, it may have lacked the power necessary to identify significant changes after accounting for the imbalances between treatment groups. One possibility to overcome this limitation may be to use a larger set of data from a multi-institutional setting or data from prospective trials (eg, RTOG 95-08). Nonetheless, this study is the largest to date to evaluate the impact of time of day on outcomes for patients with NSCLC treated for brain metastases. Our conclusions may be generalizable to other techniques for radiosurgery (ie, LINAC-based systems) because there are no randomized prospective studies to suggest a difference in LC and survival outcomes between the 2 techniques. Also, there is no evidence in the literature to suggest that the optimal time of day for treatment is different between the 2 techniques.

Future studies evaluating the impact of time of day should employ statistical methods to rationally derive a time cut-point. Moving forward, one potential solution for optimizing derivation of cut-points would be combining our statistical analysis technique with molecular studies that identify circadian rhythm–based changes in radiation sensitivity pathways such as DNA damage repair.[18-20]

Conclusions

Although earlier treatment appears to be associated with improved LC and OS, treatment time fails to remain significant when accounting for confounding patient, tumor, and treatment variables. In our series, the effect of improved outcomes for patients treated in the morning appeared to be driven by more favorable selection of patient and tumor characteristics rather than an independent effect of time alone.

REFERENCES

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. FUNDING SOURCES
  8. CONFLICT OF INTEREST DISCLOSURE
  9. REFERENCES
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